Emil Budescu¹, Mircea Stefanovici², Ioan Iacob³

The International Conference on Computational & Experimental Engineering and Sciences, Vol.11, No.3, pp. 84-84, 2009, DOI:10.3970/icces.2009.011.084

Abstract The present paper presents the issues related to the dynamic series adjustment in order to determine the probability to reach preset values of performance, in the stated period of time and of known statistical chronological series. So, with trend functions, one can approximate the variation tendency in time of the sportive performance parameter, the difficulty being, though, the weight of each dynamic series of statistical data in the probability evaluation of performance. Each dynamic series represents values of the physical and physical tests monitored over a training phase, so over a stated period of time. Based on the structural analyses… More >

A.Iwasaki¹, K.Yuguchi², A.Todoroki³, Y.Shimamura⁴

The International Conference on Computational & Experimental Engineering and Sciences, Vol.6, No.3, pp. 183-188, 2008, DOI:10.3970/icces.2008.006.183

Abstract The present study is about study on the diagnostic accuracy of the unsupervised damage diagnosis method named SI-F method. For the health monitoring of existing structures, modeling of entire structure or obtaining data sets after creating damage for training is almost impossible. This raises significant demand for development of a low-cost diagnostic method that does not require modeling of entire structure or data on damaged structure. Therefore, the present study proposes a low-cost unsupervised statistical diagnostic method for structural damage detection. The proposed method statistically diagnoses structural condition by means of investigating the change of a response surface which conducts… More >

A.H.W. Ngan¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.4, No.3, pp. 137-144, 2007, DOI:10.3970/icces.2007.004.137

Abstract When a random structure is loaded by far-field stresses, the elements inside will not be subject to the same forces because of structural inhomogeneities. Such a system represents an interesting analog to a thermal system at equilibrium -- the structural irregularities qualify for a description by a Shannon-like entropy, and there is also the usual (e.g. elastic) strain energy. When an entropy is related to energy, one immediately steps into the familiar field of statistical mechanics, but for a strained random structure, the real (Kelvin) temperature plays no role. Instead, an effective temperature exists but this is not the Kelvin… More >

Kundur Shantisagar, R. Jegadeeshwaran^*, G. Sakthivel, T. M. Alamelu Manghai

Structural Durability & Health Monitoring, Vol.13, No.3, pp. 303-316, 2019, DOI:10.32604/sdhm.2019.00355

Abstract The productivity and quality in the turning process can be improved by utilizing the predicted performance of the cutting tools. This research incorporates condition monitoring of a non-carbide tool insert using vibration analysis along with machine learning and fuzzy logic approach. A non-carbide tool insert is considered for the process of cutting operation in a semi-automatic lathe, where the condition of tool is monitored using vibration characteristics. The vibration signals for conditions such as heathy, damaged, thermal and flank were acquired with the help of piezoelectric transducer and data acquisition system. The descriptive statistical features were extracted from the acquired… More >

Chowhan S.S.¹, G.N. Shinde²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.9, No.1, pp. 67-74, 2009, DOI:10.3970/icces.2009.009.067

Abstract Feature selection, often used as a pre-processing step to machine learning, is designed to reduce dimensionality, eliminate irrelevant data and improve accuracy. Iris Basis is our first attempt to reduce the dimensionality of the problem while focusing only on parts of the scene that effectively identify the individual. Independent Component Analysis (ICA) is to extract iris feature to recognize iris pattern. Principal Component Analysis (PCA) is a dimension-reduction tool that can be used to reduce a large set of variables to a small set that still contains most of the information in the large set. Image quality is very important… More >

Sergei Bronnikov¹, Sergei Kostromin, Vyacheslav Zuev

The International Conference on Computational & Experimental Engineering and Sciences, Vol.9, No.4, pp. 207-214, 2009, DOI:10.3970/icces.2009.009.207

Abstract Kinetics of the ordered phase growth in a melted multi-component liquid crystalline mixture subjected to a deep cooling was studied using polarizing optical microscopy. The droplets of the ordered phase revealed in the optical images across the phase transition were segmented and treated statistically. In the resulting histograms, two overlapping statistical ensembles related to two main components of the mixture were recognized. These ensembles were successfully described using principles of irreversible thermodynamics and the mean droplet diameters within both ensembles were determined. Analysis of the mean droplet diameter as a function of time allowed recognition of two regimes involved in… More >

A. Joshuva¹, V. Sugumaran²

Structural Durability & Health Monitoring, Vol.13, No.2, pp. 181-203, 2019, DOI:10.32604/sdhm.2019.00287

Abstract Wind turbine blades are generally manufactured using fiber type material because of their cost effectiveness and light weight property however, blade get damaged due to wind gusts, bad weather conditions, unpredictable aerodynamic forces, lightning strikes and gravitational loads which causes crack on the surface of wind turbine blade. It is very much essential to identify the damage on blade before it crashes catastrophically which might possibly destroy the complete wind turbine. In this paper, a fifteen tree classification based machine learning algorithms were modelled for identifying and detecting the crack on wind turbine blades. The models are built based on… More >

Costas P. Providakis^1,*, Stavros E. Tsistrakis¹, Evangelos V. Liarakos¹

Structural Durability & Health Monitoring, Vol.12, No.4, pp. 257-279, 2018, DOI:10.32604/sdhm.2018.04607

Abstract In the present study a new structural health monitoring (SHM) technique is proposed as well as a new damage index based on 2-D error statistics. The proposed technique combines the electromechanical impedance technique (EMI) which is based on the use of piezoelectric Lead Zirconate Titanate (PZT) patches and Scanning Laser Doppler Vibrometry (SLDV) for damage detection purposes of concrete structures and early age monitoring. Typically the EMI technique utilizes the direct and inverse piezoelectric effect of a PZT patch attached to a host structure via an impedance analyzer that is used for both the actuation and sensing the response of… More >

A. Joshuva¹, V. Sugumaran²

Structural Durability & Health Monitoring, Vol.11, No.1, pp. 69-90, 2017, DOI:10.3970/sdhm.2017.012.069

Abstract Renewable energy sources are considered much in energy fields because of the contemporary energy calamities. Among the important alternatives being considered, wind energy is a durable competitor because of its dependability due to the development of the innovations, comparative cost effectiveness and great framework. To yield wind energy more proficiently, the structure of wind turbines has turned out to be substantially bigger, creating conservation and renovation works troublesome. Due to various ecological conditions, wind turbine blades are subjected to vibration and it leads to failure. If the failure is not diagnosed early, it will lead to catastrophic damage to the… More >

Sara Salehyar^{1, †}, Nickolas Forsch^1,†,*, Kathleen Gilbert^2,3, Alistair A. Young^3,4, James C. Perry⁵, Sanjeet Hegde⁵, Jeffrey H. Omens^1,6, Andrew D. McCulloch^1,6

Molecular & Cellular Biomechanics, Vol.16, No.3, pp. 179-183, 2019, DOI:10.32604/mcb.2019.07384

Abstract Tetralogy of Fallot (TOF) is the most common form of cyanotic congenital heart disease. Infants diagnosed with TOF require surgical interventions to survive into adulthood. However, as a result of postoperative structural malformations and long-term ventricular remodeling, further interventions are often required later in life. To help identify those at risk of disease progression, serial cardiac magnetic resonance (CMR) imaging is used to monitor these patients. However, most of the detailed information on cardiac shape and biomechanics contained in these large four-dimensional (4D) data sets goes unused in clinical practice for lack of efficient and comprehensive quantitative analysis tools. While… More >