The combination of empirical mode decomposition and minimum entropy deconvolution for roller bearing diagnostics in non-stationary operation

Diagnostics is based on the characterization of mechanical system condition and allows early detection of a possible fault. Signal processing is an approach widely used in diagnostics, since it allows directly characterizing the state of the system. Several types of advanced signal processing techniques have been proposed in the last decades and added to more conventional ones. Seldom, these techniques are able to consider non-stationary operations. Diagnostics of roller bearings is not an exception of this framework. In this paper, a new vibration signal processing tool, able to perform roller bearing diagnostics in whatever working condition and noise level, is developed on the basis of two data-adaptive techniques as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED), coupled by means of the mathematics related to the Hilbert transform. The effectiveness of the new signal processing tool is proven by means of experimental data measured in a test-rig that employs high power industrial size components.

Decomposition construction for secret sharing schemes with graph access structures in polynomial time

The purpose of this paper is to describe a new decomposition construction for perfect secret sharing schemes with graph access structures. The previous decomposition construction proposed by Stinson is a recursive method that uses small secret sharing schemes as building blocks in the construction of larger schemes. When the Stinson method is applied to the graph access structures, the number of such “small” schemes is typically exponential in the number of the participants, resulting in an exponential algorithm. Our method has the same flavor as the Stinson decomposition construction; however, the linear programming problem involved in the construction is formulated in such a way that the number of “small” schemes is polynomial in the size of the participants, which in turn gives rise to a polynomial time construction. We also show that if we apply the Stinson construction to the “small” schemes arising from our new construction, both have the same information rate.

On application of structural decomposition for process model abstraction

Real world business process models may consist of hundreds of elements and have sophisticated structure. Although there are tasks where such models are valuable and appreciated, in general complexity has a negative influence on model comprehension and analysis. Thus, means for managing the complexity of process models are needed. One approach is abstraction of business process models-creation of a process model which preserves the main features of the initial elaborate process model, but leaves out insignificant details. In this paper we study the structural aspects of process model abstraction and introduce an abstraction approach based on process structure trees (PST). The developed approach assures that the abstracted process model preserves the ordering constraints of the initial model. It surpasses pattern-based process model abstraction approaches, allowing to handle graph-structured process models of arbitrary structure. We also provide an evaluation of the proposed approach.

Efficient computation of causal behavioural profiles using structural decomposition

Identification of behavioural contradictions is an important aspect of software engineering, in particular for checking the consistency between a business process model used as system specification and a corresponding workflow model used as implementation. In this paper, we propose causal behavioural profiles as the basis for a consistency notion, which capture essential behavioural information, such as order, exclusiveness, and causality between pairs of activities. Existing notions of behavioural equivalence, such as bisimulation and trace equivalence, might also be applied as consistency notions. Still, they are exponential in computation. Our novel concept of causal behavioural profiles provides a weaker behavioural consistency notion that can be computed efficiently using structural decomposition techniques for sound free-choice workflow systems if unstructured net fragments are acyclic or can be traced back to S- or T-nets.

Facilitating query decomposition in query language modeling by association rule mining using multiple sliding windows

This paper presents a novel framework to further advance the recent trend of using query decomposition and high-order term relationships in query language modeling, which takes into account terms implicitly associated with different subsets of query terms. Existing approaches, most remarkably the language model based on the Information Flow method are however unable to capture multiple levels of associations and also suffer from a high computational overhead. In this paper, we propose to compute association rules from pseudo feedback documents that are segmented into variable length chunks via multiple sliding windows of different sizes. Extensive experiments have been conducted on various TREC collections and our approach significantly outperforms a baseline Query Likelihood language model, the Relevance Model and the Information Flow model.

Direct evidence for base-mediated decomposition of alkyl hydroperoxides (ROOH) in the gas phase

Alkyl hydroperoxides (ROOH) are attributed a key role in the biochemical oxidation of lipids during oxidative stress.1 In this chemistry ROOH compounds, where the R groups are unsaturated fatty acids, are viewed as transient ntermediates which are readily degraded, due to the lability of the RO-OH bond, to yield potentially genotoxic aldehydes and ketones.2 Generally, the decomposition of alkyl hydroperoxides is thought to be mediated by radical abstraction or electron transfer processes usually involving enzymes, transition metals, or recently, Vitamin C.3 In this paper we present the first unambiguous experimental and computational evidence for base-mediated heterolytic decomposition of simple alkyl hydroperoxides by the mechanism outlined in Scheme 1.

Base-induced decomposition of alkyl hydroperoxides in the gas phase. Part 3. Kinetics and dynamics in HO-+CH3OOH, C2H5OOH, and tert-C4H9OOH reactions

The E-CO(2) elimination reactions of alkyl hydroperoxides proceed via abstraction of an (x-hydrogen by a base: X- + (RRHCOOH)-R-1-H-2 -> HX + (RRC)-R-1-C-2=O + HO-. Efficiencies and product distributions for the reactions of the hydroxide anion with methyl, ethyl, and tert-butyl hydroperoxides are studied in the gas phase. On the basis of experiments using three isotopic analogues, HO- + CH3OOH, HO- + CD3OOH, and H18O- + CH3OOH. the overall intrinsic reaction efficiency is determined to be 80% or greater. The E(CO)2 decomposition is facile for these methylperoxide reactions, and predominates over competing proton transfer at the hydroperoxide moiety. The CH3CH2OOH reaction displays a similar E(CO)2 reactivity, whereas proton transfer and the formation of HOO- are the exclusive pathways observed for (CH3)(3)COOH, which has no (x-hydrogen. All results are consistent with the E-CO(2) mechanism, transition state structure, and reaction energy diagrams calculated using the hybrid density functional B3LYP approach. Isotope labeling for HO- + CH3OOH also reveals some interaction between H2O and HO- within the E(CO)2 product complex [H2O center dot center dot center dot CH2=O center dot center dot center dot HO-]. There is little evidence, however. for the formation of the most exothermic products H2O + CH2(OH)O-, which would arise from nuclephilic condensation of CH2=O and HO-. The results suggest that the product dynamics are not totally statistical but are rather direct after the E-CO(2) transition state. The larger HO- + CH3CH2OOH system displays more statistical behavior during complex dissociation.

Thermal stability and decomposition kinetics of styrene-butadiene rubber nanocomposites filled with different particle sized kaolinites

A series of styrene-butadiene rubber (SBR) nanocomposites filledwith different particle sized kaolinites are prepared via a latex blending method. The thermal stabilities of these clay polymer nanocomposites (CPN) are characterized by a range of techniques including thermogravimetry (TG), digital photos, scanning electron microscopy (SEM) and Raman spectroscopy. These CPN show some remarkable improvement in thermal stability compared to that of the pure SBR. With the increase of kaolinite particle size, the residual char content and the average activation energy of kaolinite SBR nanocomposites all decrease; the pyrolysis residues become porous; the crystal carbon in the pyrolysis residues decrease significantly from 58.23% to 44.41%. The above results prove that the increase of kaolinite particle size is not beneficial in improving the thermal stability of kaolinite SBR nanocomposites.

Decomposition analysis of air pollution abatement in China: empirical study for ten industrial sectors from 1998 to 2009

This study analyzes the management of air pollutant substance in Chinese industrial sectors from 1998 to 2009. Decomposition analysis applying the logarithmic mean divisia index is used to analyze changes in emissions of air pollutants with a focus on the following five factors: coal pollution intensity (CPI), end-of-pipe treatment (EOP), the energy mix (EM), productive efficiency change (EFF), and production scale changes (PSC). Three pollutants are the main focus of this study: sulfur dioxide (SO2), dust, and soot. The novelty of this paper is focusing on the impact of the elimination policy on air pollution management in China by type of industry using the scale merit effect for pollution abatement technology change. First, the increase in SO2 emissions from Chinese industrial sectors because of the increase in the production scale is demonstrated. However, the EOP equipment that induced this change and improvements in energy efficiency has prevented an increase in SO2 emissions that is commensurate with the increase in production. Second, soot emissions were successfully reduced and controlled in all industries except the steel industry between 1998 and 2009, even though the production scale expanded for these industries. This reduction was achieved through improvements in EOP technology and in energy efficiency. Dust emissions decreased by nearly 65% between 1998 and 2009 in the Chinese industrial sectors. This successful reduction in emissions was achieved by implementing EOP technology and pollution prevention activities during the production processes, especially in the cement industry. Finally, pollution prevention in the cement industry is shown to result from production technology development rather than scale merit. © 2013 Elsevier Ltd. All rights reserved.

Decomposition of toxic chemical substance management in three U.S. manufacturing sectors from 1991 to 2008

This study analyzes toxic chemical substance management in three U.S. manufacturing sectors from 1991 to 2008. Decomposition analysis applying the logarithmic mean Divisia index is used to analyze changes in toxic chemical substance emissions by the following five factors: cleaner production, end-of-pipe treatment, transfer for further management, mixing of intermediate materials, and production scale. Based on our results, the chemical manufacturing sector reduced toxic chemical substance emissions mainly via end-of-pipe treatment. In the meantime, transfer for further management contributed to the reduction of toxic chemical substance emissions in the metal fabrication industry. This occurred because the environmental business market expanded in the 1990s, and the infrastructure for the recycling of metal and other wastes became more efficient. Cleaner production is the main contributor to toxic chemical reduction in the electrical product industry. This implies that the electrical product industry is successful in developing a more environmentally friendly product design and production process.

Decomposition of the environmental Kuznets curve : scale, technique, and composition effects

This study decomposed the determinants of environmental quality into scale, technique, and composition effects. We applied a semiparametric method of generalized additive models, which enabled us to use flexible functional forms and include several independent variables in the model. The differences in the technique effect were found to play a crucial role in reducing pollution. We found that the technique effect was sufficient to reduce sulfur dioxide emissions. On the other hand, its effect was not enough to reduce carbon dioxide (CO2) emissions and energy use, except for the case of CO2 emissions in high-income countries.

Insight into the thermal decomposition of kaolinite intercalated with potassium acetate : an evolved gas analysis

The thermal decomposition process of kaolinite–potassium acetate intercalation complex has been studied using simultaneous thermogravimetry coupled with Fourier-transform infrared spectroscopy and mass spectrometry (TG-FTIR-MS). The results showed that the thermal decomposition of the complex took place in four temperature ranges, namely 50–100, 260–320, 320–550, and 650–780 °C. The maximal mass losses rate for the thermal decomposition of the kaolinite–potassium acetate intercalation complex was observed at 81, 296, 378, 411, 486, and 733 °C, which was attributed to (a) loss of the adsorbed water, (b) thermal decomposition of surface-adsorbed potassium acetate (KAc), (c) the loss of the water coordinated to potassium acetate in the intercalated kaolinite, (d) the thermal decomposition of intercalated KAc in the interlayer of kaolinite and the removal of inner surface hydroxyls, (e) the loss of the inner hydroxyls, and (f) the thermal decomposition of carbonate derived from the decomposition of KAc. The thermal decomposition of intercalated potassium acetate started in the range 320–550 °C accompanied by the release of water, acetone, carbon dioxide, and acetic acid. The identification of pyrolysis fragment ions provided insight into the thermal decomposition mechanism. The results showed that the main decomposition fragment ions of the kaolinite–KAc intercalation complex were water, acetone, carbon dioxide, and acetic acid. TG-FTIR-MS was demonstrated to be a powerful tool for the investigation of kaolinite intercalation complexes. It delivers a detailed insight into the thermal decomposition processes of the kaolinite intercalation complexes characterized by mass loss and the evolved gases.

Turbulence measurements in a shallow tidal estuary : analysis based on triple decomposition

In an estuary, mixing and dispersion are the result of the combination of large scale advection and small scale turbulence which are both complex to estimate. A field study was conducted in a small sub-tropical estuary in which high frequency (50 Hz) turbulent data were recorded continuously for about 48 hours. A triple decomposition technique was introduced to isolate the contributions of tides, resonance and turbulence in the flow field. A striking feature of the data set was the slow fluctuations which exhibited large amplitudes up to 50% the tidal amplitude under neap tide conditions. The triple decomposition technique allowed a characterisation of broader temporal scales of high frequency fluctuation data sampled during a number of full tidal cycles.