The use of fuzzy logic and neural networks models for sensory properties prediction from process and structure parameters of knitted fabrics

In a competitive business environment, the textile industrialists intend to propose diversified products according to consumers preference. For this purpose, the integration of sensory attributes in the process parameters choice seems to be a useful alternative. This paper provides fuzzy and neural models for the prediction of sensory properties from production parameters of knitted fabrics. The prediction accuracy of these models was evaluated using both the root mean square error (RMSE) and mean relative percent error (MRPE). The results revealed the models ability to predict tactile sensory attributes based on the production parameters. The comparison of the prediction performances showed that the neural models are slightly powerful than the fuzzy models.     

Investigation of the viscoelastic response of high temperature AS4‐12K/RP46 composites using a micromechanical approach

The viscoelastic behavior of a RP46 polyimide resin is characterized at high temperature and the results are used within a micromechanical model to predict the viscoelastic response of a RP46 based carbon fiber composite. The creep master curve of the neat resin is obtained using the time temperature superposition principle (TTSP) from creep tests at three different temperatures, namely 180, 220, and 270°C. The viscoelastic behavior of RP46 is modeled based on Schapery's single integral constitutive equation whose Prony Series coefficients are obtained from the master curve. The acquired properties are then incorporated into a Simplified Unit Cell Micromechanical model to study the creep response of a RP46 resin based composite system. The advantage of this particular micromechanical model lies in its ability to give closed form expressions for the effective viscoelastic response of unidirectional composites as well as each of their constituents. Two types of nonlinearities were observed, one due to stress and the other due to temperature. Both of these nonlinearities can be modeled through the use of proper coefficients in the constitutive equation of the matrix material. The model predictions are found to be in good agreement with experimental results obtained from tests conducted on the RP46 resin based composite system. POLYM. COMPOS., 37:1407–1414, 2016. © 2014 Society of Plastics Engineers     

An investigation of the damage mechanisms and fatigue life diagrams of flax fiber-reinforced polymer laminates

In this paper we investigated the fatigue damage of a unidirectional flax-reinforced epoxy composite using infrared (IR) thermography. Two configurations of flax/epoxy composites layup were studied namely, [0]₁₆ unidirectional ply orientation and [±45]₁₆. The high cycle fatigue strength was determined using a thermographic criterion developed in a previous study. The fatigue limit obtained by the thermographic criterion was confirmed by the results obtained through conventional experimental methods (i.e., Stress level versus Number of cycles to failure). Furthermore, a model for predicting the fatigue life using the IR thermography was evaluated. The model was found to have a good predictive value for the fatigue life. In order to investigate the mechanism of damage initiation in flax/epoxy composites and the damage evolution, during each fatigue test we monitored the crack propagation for a stress level and at different damage stages, a direct correlation between the percentage of cracks and the mean strain was observed.     

A micromechanical approach for the prediction of the time-dependent failure of high temperature polymer matrix composites

In the present study, a novel micromechanical approach is introduced to study the time-dependent failure of unidirectional polymer matrix composites. The main advantage of the present micromechanical model lies in its ability to give closed-form solutions for the effective nonlinear response of unidirectional composites and to predict the material response to any combination of shear and normal loading. The creep failure criterion is expressed in terms of the creep failure functions of the viscoelastic matrix material. The micromechanical model is also used to calculate these creep failure functions from the knowledge of the creep behavior of the composite material in only transverse and shear loadings, thus eliminating the need for any further experimentation. The composite material used in this study is T300/934, which is suitable for service at high temperatures in aerospace applications. The use of micromechanics can give a more accurate insight into the failure mechanisms of the composite materials in particular at high temperatures where the general behavior of the polymer matrix composite is governed by matrix viscoelasticity and the time-dependent failure of the matrix is a localized phenomenon. The obtained creep failure stresses are found to be in reasonable agreement with the experimental data.     

Short vs. long column behavior of pultruded glass-fiber reinforced polymer composites

Analytical and experimental studies were conducted for the purpose of establishing a distinguishing criterion between short and long FRP composite column behaviors. The results of investigating 24 full-scale GFRP composite columns are presented. The experimental studies utilized specimens with commonly used ‘Universal’ and ‘Box’ cross-sections which were manufactured by the pultrusion process using E-glass fibers in various forms as reinforcement and polyester and vinylester as binding matrices. The effective slenderness ratios (L/r) of the investigated columns were 3.79, 32.7, 47.9, 63.1 and 75.4 for the ‘Universal’ section and 9.38, 53.9 and 78.9 for the ‘Box’ section. The specimen lengths were 18 inches (0.46 m), 8 foot (2.44 m), 12 foot (3.66 m), 16 foot (4.88 m) and 19.25 foot (5.87 m). All columns were tested in a vertical position and under compressive axial static loading and the fundamental pinned–pinned end-conditions. The columns’ compressive strains, buckling and crippling loads, lateral displacements, initial curvatures, and modes of failure were documented during the course of this investigation. Orthotropic mechanical properties of the composites were experimentally obtained utilizing 44 coupons cut from the column specimens. Analytically, Euler's formula was employed to obtain critical loads for the slender columns. For short columns, the classical plate theory was used to predict columns’ buckling loads. Based on experimental evaluations and analytical results, a slenderness ratio based criterion was established for distinguishing between short and long composite column behaviors. Further conclusions and design recommendations were made.     

CT scan contrast enhancement using singular value decomposition and adaptive gamma correction

We propose in this paper a new enhancement algorithm dedicated to dark computed tomography (CT) scan based on discrete wavelet transform with singular value decomposition (DWT–SVD) followed by adaptive gamma correction (AGC). Discrete wavelet transform (DWT) is considered to decompose the input dark CT image in four sub-bands. Singular value decomposition (SVD) is used in order to compute the corresponding singular value matrix of low–low (LL) sub-band image. The enhanced LL sub-band is determined by scaling the singular value matrix of original LL sub-band by an adequate correction factor, followed by inverse SVD. For a further contrast improvement, the new enhanced LL sub-band image is processed using an AGC algorithm. Finally, the obtained LL sub-band image undergoes inverse DWT together with the unprocessed sub-bands to generate the final enhanced image. This proposed method has the advantage of being fully automatic and could be applied for dark input images with either low or moderate contrast. Different dark CT images are considered to compare the performance of our proposed method to three other enhancement techniques using both objective and subjective assessments. Simulation results show that our proposed algorithm consistently produces good contrast enhancement, with best brightness and edges details conservation and with minimum added distortions to the enhanced CT images.     

Impact of spare parts remanufacturing on the operation and maintenance performance of offshore wind turbines: a multi-agent approach

Offshore wind farms are a growing source of energy, which aims to ensure a clean energy with a low environmental impact. In this context, this paper investigates opportunities of the turbine gearbox end of life-cycle to improve the operation and maintenance strategies. We determine the impact of spare part policy based on the remanufacturing of gearboxes recovered after each replacement. The remanufacturing implementation allows the extension of the gearbox life-cycle and involves a perfect organization and coordination between maintenance, monitoring, operation and spare part supply chain to determine the best way to use each gearbox of each wind turbine. In this paper, we present a multi-agent based approach to analyze the impact of the spare parts remanufacturing strategy on the performance of an offshore wind farm in term of total cost and carbon footprint.     

Sensor fault detection and isolation filter for polytopic LPV systems: A winding machine application

In this paper, a fault diagnosis method is developed for a particular class of nonlinear systems described by a polytopic linear parameter varying (LPV) formulation. The main contribution consists in the synthesis of an accurate fault detection and isolation (FDI) filter and also a sensor fault magnitude estimation with a quality factor. This quality factor of the filter underlines if the fault estimation can be used or not. Stability conditions of the polytopic LPV filter are studied by ensuring poly-quadratic stability with Linear Matrix Inequality (LMI) representation. The effectiveness of this global FDI scheme through LPV modelization, filter design and stability analysis, is illustrated on a real winding machine under multiple sensor faults.