Flaw detection in radiographic weldment images using morphological watershed segmentation technique

In this paper, the concept of application of morphological multistage watershed segmentation for detection of flaws in radiographic weld images is discussed. It is simple and intuitive and always produces a complete division of the image. The multistage watershed segmentation used here reduces the problem of over segmentation besides generating boundaries with very less deviation from their original position. Two-stage water segmentation is implemented here. At the first stage, watershed transform is applied to an X-ray image and the resultant mosaic image pattern is further thresholded by Otsu's thresholding method and converted into the binary image. Then, morphology and top-hat transformation is applied on binary image to separate partially overlapping objects. Euclidean distance map is calculated for each basin to label resultant segments uniquely and to separate ridges. This follows the second stage of watershed segmentation to obtain better-defined boundaries while removing over-segmented regions. Watershed segmentation algorithm has been able to detect flaws like slag inclusions and wormholes-type weld flaws. It shows all defects with reasonable accuracy having close contours. Similarly, small cavities are also highlighted successfully.     

Structural,morphological and microhardness characterization in polymer complex of laser dye rhodamine (Rh6G) doped polymethyl methacrylate

Polymer systems have various contents of rhodamine (Rh6G) doped Polymethyl methacrylate (PMMA) prepared by solution cast method. The structural and morphological properties were studied by Differential Scanning calorimetry (DSC), Fourier Transform Infrared spectroscopy (FTIR) Scanning Electron Microscopy (SEM) and X-ray diffraction methods. The induced effect on the strength of rhodamine (Rh6G) doped Polymethyl methacrylate (PMMA) samples were studied by measuring the surface microhardness using the Vicker’s microhardness tester. Significant changes were observed in the Vickers microhardness number (H_v)     

Decision tree approach for classification and dimensionality reduction of electronic nose data

This paper presents a decision tree approach using two different tree models, C4.5 and CART, for use in the classification and dimensionality reduction of electronic nose (EN) data. The decision tree is a tree structure consisting of internal and terminal nodes which process the data to ultimately yield a classification. The decision tree is proficient at both maintaining the role of dimensionality reduction and at organizing optimally sized classification trees, and therefore it could be a promising approach to analyze EN data. In the experiments conducted, six sensor response parameters were extracted from the dynamic sensor responses of each of the four metal oxide gas sensors. The six parameters observed were the rising time (T_r), falling time (T_f), total response time (T_t), normalized peak voltage change (y_p,n), normalized curve integral (C_I), and triangle area (T_A). One sensor parameter from each metal oxide sensor was used for the classification trees, and the best classification accuracy of 97.78% was achieved by CART using the C_I parameter. However, the accuracy of CART was improved using all of the sensor parameters as inputs to the classification tree. The improved results of CART, having an accuracy of 98.89%, was comparable to that of two popular classifiers, the multilayer perceptron (MLP) neural network and the fuzzy ARTMAP network (accuracy of 98.89%, and 100%, respectively). Furthermore, as a dimensionality reduction method the decision tree has shown a better discrimination accuracy of 100% for the MLP classifier and 98.89% for the fuzzy ARTMAP classifier as compared to those achieved with principle component analysis (PCA) giving 81.11% and 97.78%, and a variable selection method giving 92.22% and 93.33% (for the same MLP and fuzzy ARTMAP classifiers). Therefore, a decision tree could be a promising technique for a pattern recognition system for EN data in terms of two functions; as classifier which is an optimally organized classification tree, and as dimensionality reduction method for other pattern recognition techniques.     

Optimization of cellulases production by Trichoderma citrinoviride on marc of Artemisia annua and its application for bioconversion process

The production of cellulases by Trichoderma citrinoviride fermented on marc of Artemisia annua, and bioconversion of the same marc by produced cellulase system was studied. The effects of pretreatments, substrate concentration, particle size, initial pH, temperature and concentration of the medium components on production of FPase, endoglucanase and β-glucosidase were monitored and comparatively evaluated. Among the three pretreatment processes, alkali hydrolysis with autoclaving was found to be most suitable for production of all the three enzymes. Optimum production of FPase, endoglucanase and β-glucosidase was obtained at 96 h, 96 h and 72 h of fermentation period, respectively. Substrate concentration of 1% with particle size between 200 μm and 475 μm gave the higher yields. Higher production of all the three enzymes was obtained with initial pH value of 5.5, temperature of 28 °C and 75% of mineral salt solution. Partially purified enzyme system obtained by optimized fermentation procedure, was applied for saccharification. Forty six percent of saccharification was noticed after 48 h of incubation on alkali hydrolyzed and autoclaved substrate which was 3.26 fold more than that of unpretreated substrate.     

Sequence of Phase Formation in Chemically Derived Ferroelectric Lead Zirconate Titanate Pb(Zr0.4Ti0.6)O3 Thin Films

A qualitative model for the sequence of phase transforma-tions leading to perovskite phase formation in sol–gel-derived PZT thin films is presented. It is suggested that for sol–gel-derived Pb(Zr_xTi_1–x)O₃ (x = 0.4) thin films, prepared using the molecularly modified alkoxide precursors (MMAP) approach, complete (or partial) conversion of the originally amorphous film into a "pyrochlore" phase, although possible, may not be necessary. Differences between the sequence of phase formation encountered in the tradi-tional (oxide-mix) synthesis and that in chemically derived ceramics are discussed. The sequence of phase formation in these thin films also appears to be intertwined with the texture development in that a (111) PZT texture develop-ment appears to be controlled by nucleation of the perovs-kite phase, assisted by a solid-phase epitaxial effect, and the (100)/(001) texture appears to be growth controlled.x     

Experimental investigation of dry,wet and cryogenic boring of AA 7075 alloy

In this research work, an attempt has been carried out to examine (investigate) and study the dry, wet and cryogenic boring of AA 7075 alloy, which is predominantly used in transport applications in defense (aeronautical parts), oceanic and automaker industries. To ensure direct supply of the coolant, and real-time measurement of cutting temperature a modified boring bar is used (modification is carried out using EDM to accommodate placement of a thermocouple to obtain real-time measurement of temperature readings during the boring cycle). It is observed that during cryogenic boring of AA 7075 alloy there is a considerable reduction in the cutting force (F_c), cutting temperature (T_c) and surface roughness (R_a) by 56.16%, 84.70%, 58.98% compared to dry boring and 48.43%, 80.70%, 34.70% compared to wet boring, respectively. Decrease in F_c and T_c leads to a reduction in high stresses at localized points during machining and in turn curtail wear in workpiece and tool. Lubrication provided by cryogenic fluids also plays a sizable role in reduction of F_c and T_c. Reduction in lower F_c and T_c has a glaring effect on the surface characteristics of the hole produced during the boring process. Tool wear is reduced in cryogenic boring by 36.96% and 17.57% compared to dry and wet boring, respectively. Taguchi and ANOVA was carried out which helped in determining feed as an important parameter with respect to F_c and R_a during boring of AA 7075 under dry, wet and cryogenic conditions whereas speed as an important parameter in determining T_c in dry and wet conditions and feed for T_c in cryogenic boring condition. TOPSIS analysis highlighted speed of 770 rpm and feed of 0.055 mm/min as the most closest to ideal solution for all three different cutting conditions. Surface morphology study after boring of AA 7075 highlighted better surface characteristics in cryogenic bored surface compared to dry and wet boring. Roughness measured in AFM for tool used in boring highlighted a decrease in 86.79% and 66.01% in cryogenic boring in juxtaposition with dry and wet boring, respectively. A surge in compressive residual stress is observed in cryogenic bored surface by 10.41% and 3.5% in juxtaposition with dry and wet boring, respectively, highlighting an abatement in tensile residual stress and better workpiece integrity as compared to dry and wet boring conditions.     

Graphene-Reinforced Aluminum Matrix Composites: A Review of Synthesis Methods and Properties

Graphene-reinforced aluminum (Gr-Al) matrix nanocomposites (NCs) have attracted strong interest from both research and industry in high-performance weight-sensitive applications. Due to the vastly different bonding characteristics of the Al matrix (metallic) and graphene (in-plane covalent?+?inter-plane van der Waals), the graphene phase has a general tendency to agglomerate and phase separate in the metal matrix, which is detrimental for the mechanical and chemical properties of the composite. Thus, synthesis of Gr-Al NCs is extremely challenging. This review summarizes the different methods available to synthesize Gr-Al NCs and the resulting properties achieved in these NCs. Understanding the effect of processing parameters on the realized properties opens up the possibility of tailoring the synthesis methods to achieve the desired properties for a given application.