Energy inefficiency diagnosis in industrial process through one-class machine learning techniques

In the era of Industry 4.0, the ease of access to precise measurements in real-time and the existence of machine-learning (ML) techniques will play a vital role in building practical tools to isolate inefficiencies in energy-intensive processes. This paper aims at developing an abnormal event diagnosis (AED) tool based on ML techniques for monitoring the operation of industrial processes. This tool makes it easier for operators to accomplish their tasks and to make quick and accurate decisions to ensure highly efficient processes. One of the most popular ML techniques for AED is the multivariate statistical control (MSC) method; it only requires the dataset of the normal operating conditions (NOC) to detect and identify the variables that contribute to abnormal events (AEs). Despite the popularity of MSC, it is challenging to select the appropriate method for detecting and isolating all possible abnormalities a complex industrial process can experience. To address this limitation and improve efficiency, we have developed a generic methodology that integrates different ML techniques into a unified multiagent based approach, the selected ML techniques are supposed to be built using only the normal operating condition. For the sake of demonstration, we chose a combination of two ML methods: principal component analysis and k-nearest neighbors (k-NN). The k-NN was integrated into the proposed multiagent to take into account the nonlinearity and multimodality that frequently occur in industrial processes. In addition, we modified a k-NN method proposed in the literature to reduce computation time during real-time detection and isolation. Finally, the proposed methodology was successfully validated to monitor the energy efficiency of a reboiler located in a thermomechanical pulp mill.

     

Spatiotemporal evolution of the El Biar landslide (Algiers): new field observation data constrained by ground-penetrating radar investigations

Bulletin of Engineering Geology and the Environment - A better understanding of the spatiotemporal evolution of landslides in urban zones is a key factor in assessing the risk of future slides...     

Road crash fatality rates in France: A comparison of road user types,taking account of travel practices

Background

Travel practices are changing: bicycle and motorized two-wheeler (MTW) use are rising in some of France’s large cities. These are cheaper modes of transport and therefore attractive at a time of economic crisis, but they also allow their users to avoid traffic congestion. At the same time, active transport modes such as walking and cycling are encouraged because they are beneficial to health and reduce pollution. It is therefore important to find out more about the road crash risks of the different modes of transport. To do this, we need to take account of the number of individuals who use each, and, even better, their travel levels.

Method

We estimated the exposure-based fatality rates for road traffic crashes in France, on the basis of the ratio between the number of fatalities and exposure to road accident risk. Fatality data were obtained from the French national police database of road traffic casualties in the period 2007–2008. Exposure data was estimated from the latest national household travel survey (ENTD) which was conducted from April 2007 to April 2008. Three quantities of travel were computed for each mode of transport: (1) the number of trips, (2) the distance traveled and (3) the time spent traveling. Annual fatality rates were assessed by road user type, age and sex.

Results

The overall annual fatality rates were 6.3 per 100 million trips, 5.8 per billion kilometers traveled and 0.20 per million hours spent traveling. The fatality rates differed according to road user type, age and sex. The risk of being killed was 20 to 32 times higher for motorized two-wheeler users than for car occupants. For cyclists, the risk of being killed, both on the basis of time spent traveling and the number of trips was about 1.5 times higher than for car occupants. Risk for pedestrians compared to car occupants was similar according to time spent traveling, lower according to the number of trips and higher according to the distance traveled. People from the 17–20 and 21–29 age groups and those aged 70 and over had the highest rates. Males had higher rates than females, by a factor of between 2 and 3.

Conclusion

When exposure is taken into account, the risks for motorized two-wheeler users are extremely high compared to other types of road user. This disparity can be explained by the combination of speed and a lack of protection (except for helmets). The differential is so great that prevention measures could probably not eliminate it. The question that arises is as follows: with regard to public health, should not the use of MTW, or at least of motorcycles, be deterred? The difference between the fatality risk of cyclists and of car occupants is much smaller (1.5 times higher); besides, there is much room for improvements in cyclist safety, for instance by increasing the use of helmets and conspicuity equipment. Traffic calming could also benefit cyclists, pedestrians and perhaps moped users.     

Hydrogen production by hybrid system and its conversion by fuel cell in Algeria; Djanet

In this work we present a scenario of wind and solar energy production and seasonal energy storage producing Hydrogen in Djanet (East-South of Algeria). In addition we suppose assume the use of a set of fuel cells which are connected to the grid to provide a supply of energy when needed afterwards. The aim of this primary study is giving an alternative solution for the electric production in Djanet, which is mainly based on diesel generator. For that we made an investigation to highlight the potential of renewable energy production in this region. To ascertain feasibility of one hybrid system, we made energetic assessment considering the real climatic conditions of Djanet.     

Ion Acoustic Solitary Waves and Double-Layers in a Plasma with Nonthermal Electrons and Positrons

The effects of nonthermal electron distribution and ion temperature are incorporated in the investigation of nonlinear ion acoustic waves in a pair-ion plasma. Sagdeev pseudo- potential method which takes into account the full nonlinearity of the plasma equations is used to study solitary wave solutions. It is shown that there is a region in parameter space where both negative and positive potential can coexist. For the fixed value of nonthermal electrons, it is found that the effect of increase in ion temperature is to reduce the range of co-existence of compressive and rarefactive solitons. Particular concentration of nonthermal electrons results in disappearance of rarefactive solitons while the decrease in ion temperature, at this concentration restores the lost rarefactive solitons. Also, the existence of rarefactive double layers solitons is investigated. It is found that the nonthermal electrons and ion-temperature play significant role in determining the region of the existence of double layers.     

Study of morphological and mechanical performance of amine‐cured glassy epoxy–clay nanocomposites

The effect of three different alkylammonium‐modified montmorillonite on morphological and mechanical properties of glassy epoxy‐amine nanocomposites is reported. Small amounts of clays <10 phr (part per hundred of resin) were used in each system of nanocomposite. The morphology of the prepared nanocomposites was performed by means of X‐ray diffraction and transmission electron microscopy. Differential scanning calorimetry (DSC) was used to investigate the glass transition temperatures (T_g). Mechanical properties were based on tensile characteristics (Young's modulus), impact strength, and fracture toughness. The measured moduli were compared to theoretical predictions. Scanning electron microscopy was used to study the morphological structure of the fracture surfaces of impacted specimens. It was found that at a low content of 2 phr (1.2 wt %) of nanoclays, the impact strength and the fracture toughness were improved by 77 and 90% respectively, comparatively to the neat epoxy, whereas DSC revealed a reduction of the T_g of nanocomposites. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

Investigating the impact of Cloisite® 15A nanoclays on the diffusivity of Irganox 1035 antioxidant in high-density polyethylene nanocomposite

Knowing the diffusion coefficients of antioxidants in packaging materials is essential to assess their effectiveness in protecting materials against oxidation, but also to prevent their eventual migration to food. In this work, the diffusion of a commercial phenolic antioxidant (Irganox 1035) was measured experimentally in pristine high-density polyethylene (HDPE) and in HDPE nanocomposite filled with 3 wt% of nanoclays (Cloisite® 15A). Diffusion experiments were performed using the Roe's method between 60 and 100°C. The local concentration of Irganox1035 in each film was measured by UV–Vis spectroscopy from the UV absorbance at 282 nm. The adjustment of the experimental data by Fick's second law allowed us to deduce the values of the diffusion coefficient of Irganox1035 at each temperature and to show that the temperature dependence of this coefficient obeys an Arrhenius' law. It is shown that the incorporation of 3 wt% of Cloisite®15A into HDPE significantly hinders the diffusion of Irganox 1035 and increases its activation energy. Several mechanistic assumptions could explain this result, first the increase in the tortuosity of diffusion paths, but also the possible establishment of strong intermolecular interactions between the antioxidant and some chemical groups on the nanofiller surface, or even the formation of an interphase with reduced molecular mobility around the nanofillers.     

Intelligent Open Switch Fault Detection for Power Converter in Wind Energy System

This paper proposes a simple and fast fuzzy logic-based open switch fault detection method for rotor side converter (RSC) in doubly fed induction generator (DFIG) wind turbine system. In the proposed scheme, only the mean values of the three-phase rotor currents are used to identify the power switch in which the open-circuit fault has occurred.

The wind energy conversion system model developed for the design and evaluation of the proposed fault detection technique including three principal controls. the first control ensure the regulation of the electromagnetic torque and the reactive stator power (named Rotor Side Converter (RSC) control), the second regulates the DC-link voltage at the desired level (named Grid Side Converter (GSC) control) and in order to achieve maximum power at any wind speed condition a maximum power point tracking (MPPT) control strategy has been used. The simulation model was developed in MATLAB/Simulink environment. The results show that the proposed fault detection scheme is able to rapidly and effectively identify open switch faults among other fault types in a time less than one period.     

The Microstructure,Texture and Mechanical Properties of Friction Stir Welded Aluminum Alloy

Russian Journal of Non-Ferrous Metals - The microstructure and texture of 7075-T6 FSW weld with optimal parameters are investigated using optical microscopy, electron back scatter diffraction and...