Multi-step ahead direct prediction for the machine condition prognosis using regression trees and neuro-fuzzy systems

This paper presents an approach to predict the operating conditions of machine based on classification and regression trees (CART) and adaptive neuro-fuzzy inference system (ANFIS) in association with direct prediction strategy for multi-step ahead prediction of time series techniques. In this study, the number of available observations and the number of predicted steps are initially determined by using false nearest neighbor method and auto mutual information technique, respectively. These values are subsequently utilized as inputs for prediction models to forecast the future values of the machines’ operating conditions. The performance of the proposed approach is then evaluated by using real trending data of low methane compressor. A comparative study of the predicted results obtained from CART and ANFIS models is also carried out to appraise the prediction capability of these models. The results show that the ANFIS prediction model can track the change in machine conditions and has the potential for using as a tool to machine fault prognosis.

Spectroscopic and structural characterization of pascoite

Pascoite mineral having yellow-orange colour of Colorado, USA origin has been characterized by EPR, optical and NIR spectroscopy. The colour dark red-orange to yellow-orange colour of the pascoite indicates that the mineral contain mixed valency of vanadium. The optical spectrum exhibits a number of electronic bands due to presence of VO(II) ions in the mineral. From EPR studies, the parameters of g, A are evaluated and the data confirm that the ion is in distorted octahedron. Optical absorption studies reveal that two sets of VO(II) is in distorted octahedron. The bands in NIR spectra are due to the overtones and combinations of water molecules.

Silylation of layered double hydroxides via an induced hydrolysis method

A series of layered double hydroxides (LDHs) based composites were synthesized by using induced hydrolysis silylation method (IHS), surfactant precursor method, in-situ coprecipitation method, and direct silylation method. Their structures, morphologies, bonding modes and thermal stabilities can be readily adjusted by changing the parameters during preparation and drying processing of the LDHs. The characterization results show that the direct silylation reaction cannot occur between the dried LDHs and 3-aminopropyltriethoxysilane (APS) in an ethanol medium. However, the condensation reaction can proceed with heating process between adsorbed APS and LDHs plates. While using wet state substrates with and without surfactant and ethanol as the solvent, the silylation process can be induced by hydrolysis of APS on the surface of LDHs plates. Surfactants improve the hydrophobicity of the LDHs during the process of nucleation and crystallization, resulting in fluffy shaped crystals; meanwhile, they occupy the surface –OH positions and leave less “free –OH” available for the silylation reaction, favoring formation of silylated products with a higher population in the hydrolyzed bidentate (T2) and tridentate (T3) bonding forms. These bonding characteristics lead to spherical aggregates and tightly bonded particles. All silylated products show higher thermal stability than those of pristine LDHs.

Design, fabrication and characterization of PCL electrospun scaffolds—a review

The expanding interest in electrospinning fibers for bioengineering includes a significant use of polyesters, including poly(3-caprolactone) (PCL). This review summarizes literature on PCL and selected blends, and provides extensive descriptions of the broad range of parameters used in manufacturing such electrospun fibers. Furthermore the chemical, physical and biological approaches for characterizing the electrospun material are described and opinions offered on important information to include in future publications with this electrospun material.