Search results

The Embedded GPS/INS System (EGI) has been used more widely as central navigation equipment of aircraft. For certain cases needing high attitude accuracy, star sensor can be integrated with EGI to improve attitude performance. Since the filtering‐correction loop has already built in finished EGI product, centralized or federated Kalman filter is not applicable for integrating EGI with star sensor; it is a challenge to design multi‐sensor information fusion algorithm suitable for this situation. The purpose of this paper is to present a double‐layer fusion scheme and algorithms to meet the practical need of constructing integrated multi‐sensor navigation system by star sensor assisting finished EGI unit.

The alternate fusion algorithms for asynchronous measurements and the sequential fusion algorithms for synchronous measurements are presented. By combining alternate filtering and sequential filtering algorithms, a kind of double‐layer fusion algorithms for multi‐sensors is proposed and validated by semi‐physical test in this paper.

The double‐layer fusion algorithms represent a filtering strategy for multiple non‐identical parallel sensors to assist INS, while the independent estimation‐correction loop in EGI is still maintained. It has significant benefits in updating original navigation system by integrating new sensors.

The approach described in this paper can be used in designing similar multi‐sensor information fusion navigation system composed by EGI and various kinds of sensors, so as to improve the navigation performance.

Compared with conventional approach, in the situation that centralized and federated Kalman filter are not applicable, the double‐layer fusion scheme and algorithms give an external filtering strategy for measurements of finished EGI unit and star sensors.

Aspect-based sentiment analysis (ASA) is a task of sentiment analysis that requires predicting aspect sentiment polarity for a given sentence. Many traditional techniques use graph-based mechanisms, which reduce prediction accuracy and introduce large amounts of noise. The other problem with graph-based mechanisms is that for some context words, the feelings change depending on the aspect, and therefore it is impossible to draw conclusions on their own. ASA is challenging because a given sentence can reveal complicated feelings about multiple aspects.

This research proposed an optimized attention-based DL model known as optimized aspect and self-attention aware long short-term memory for target-based semantic analysis (OAS-LSTM-TSA). The proposed model goes through three phases: preprocessing, aspect extraction and classification. Aspect extraction is done using a double-layered convolutional neural network (DL-CNN). The optimized aspect and self-attention embedded LSTM (OAS-LSTM) is used to classify aspect sentiment into three classes: positive, neutral and negative.

To detect and classify sentiment polarity of the aspect using the optimized aspect and self-attention embedded LSTM (OAS-LSTM) model. The results of the proposed method revealed that it achieves a high accuracy of 95.3 per cent for the restaurant dataset and 96.7 per cent for the laptop dataset.

The novelty of the research work is the addition of two effective attention layers in the network model, loss function reduction and accuracy enhancement, using a recent efficient optimization algorithm. The loss function in OAS-LSTM is minimized using the adaptive pelican optimization algorithm, thus increasing the accuracy rate. The performance of the proposed method is validated on four real-time datasets, Rest14, Lap14, Rest15 and Rest16, for various performance metrics.

Prefabricated technology is gradually being applied to the construction of subway stations due to its characteristic of mechanization. However, the prefabricated subway station in China is in the initial stage of development, which is prone to construction safety issues. This study aims to evaluate the construction safety risks of prefabricated subway stations in China and formulate corresponding countermeasures to ensure construction safety.

A construction safety risk evaluation index system for the prefabricated subway station was established through literature research and the Delphi method. Furthermore, based on the structure entropy weight method, matter-element theory and evidence theory, a hybrid evaluation model is developed to evaluate the construction safety risks of prefabricated subway stations. The basic probability assignment (BPA) function is obtained using the matter-element theory, the index weight is calculated using the structure entropy weight method to modify the BPA function and the risk evaluation level is determined using the evidence theory. Finally, the reliability and applicability of the evaluation model are verified with a case study of a prefabricated subway station project in China.

The results indicate that the level of construction safety risks in the prefabricated subway station project is relatively low. Man risk, machine risk and method risk are the key factors affecting the overall risk of the project. The evaluation results of the first-level indexes are discussed, and targeted countermeasures are proposed. Therefore, management personnel can deeply understand the construction safety risks of prefabricated subway stations.

This research fills the research gap in the field of construction safety risk assessment of prefabricated subway stations. The methods for construction safety risk assessment are summarized to establish a reliable hybrid evaluation model, laying the foundation for future research. Moreover, the construction safety risk evaluation index system for prefabricated subway stations is proposed, which can be adopted to guide construction safety management.

Gives introductory remarks about chapter 1 of this group of 31 papers, from ISEF 1999 Proceedings, in the methodologies for field analysis, in the electromagnetic community. Observes that computer package implementation theory contributes to clarification. Discusses the areas covered by some of the papers ‐ such as artificial intelligence using fuzzy logic. Includes applications such as permanent magnets and looks at eddy current problems. States the finite element method is currently the most popular method used for field computation. Closes by pointing out the amalgam of topics.

The high specific strength makes magnesium alloys have a wide range of applications in aerospace, military, automotive, marine and construction industries. However, its poor corrosion resistance and weldability have limited its development and application. Friction stir welding (FSW) can effectively avoid the defects of fusion welding. However, the microstructure, mechanical properties and corrosion behavior of FSW joints in magnesium alloys vary among different regions. The purpose of this paper is to review the corrosion of magnesium alloy FSW joints, and to summarize the protection technology of welded joints.

The corrosion of magnesium alloy FSW joints includes electrochemical corrosion and stress corrosion. This paper summarizes corrosion protection techniques for magnesium alloys FSW joints, focusing on composition, microstructure changes and surface treatment methods.

Currently, this research is mainly focused on enhancing the corrosion resistance of magnesium alloy FSW joints by changing compositions, structural modifications and surface coating technologies. Refinement of the grains can be achieved by adjusting welding process parameters, which in turn minimizes the effects of the second phase on the alloy’s corrosion resistance.

This paper presents a comprehensive review on the corrosion and protection of magnesium alloys FSW joints, covering the latest research advancements and practical applications. It aims to equip researchers with a better insight into the field and inspire new studies on this topic.

The purpose of this paper is to create a new method of prognosis based on remaining useful life (RUL) prediction for degradation assessment.

In the present paper the authors describe a new method of prognosis to improve the accuracy of forecasting the system state. This framework of forecasting integrates the model-based information and the hybrid approach, which employs the structured residuals in the first part and the particle filter in the second part.

The performance of the suggested fusion framework is employed to predict the RUL of battery pack in hybrid electric vehicle. The results show that the proposed method is plausible due to the good prediction of RUL, and can be effectively applied to many systems for prognosis.

In this study the authors illustrate how the suggested method can provide an accurate prediction of the RUL over conventional data-driven methods without physical model and classical particle filter with a single damage model.

The purpose of this paper is to optimize the performance of direct methanol fuel cells for portable applications by combining a non‐linear, fully coupled circuit model and a stochastic optimization procedure.

A novel non‐linear equivalent circuit that accounts for electrochemical reactions and charge generation inside catalyst layers, electronic and protonic conduction, methanol crossover through the membrane, mass transport of reactants inside diffusion layers is presented. The discharge dynamic of the fuel cell, depending on the initial methanol concentration and on the load profile, is modelled by using the mass conservation equation. The equivalent circuit is interfaced to a stochastic optimization procedure in order to maximize the battery duration while minimizing fuel crossover.

In the proposed circuit scheme, unlike semi‐empirical models, lumped circuit parameters are derived directly from mass transport and electric equations in order to fully describe the dynamic performance of the fuel cell. Physical and geometrical parameters are optimized in order to improve the system runtime. It is shown that a combined use of fuel cells and lithium batteries can improve the runtime of portable electronic devices compared to traditional supply systems based on lithium batteries only.

The one‐dimensional model of the micro fuel cell does not take into account possible transverse mass and electric charge flows in the fuel cell layers; most of the geometric and physics model parameters cannot be estimated from direct in situ or ex situ measurements.

Direct methanol fuel cells are nowadays a promising technology for replacing or complementing lithium batteries due to their high energy density. Most limiting features of direct methanol fuel cells are the fuel crossover and its slow oxidation kinetics. By using the proposed approach, fuel cell parameters can be optimized in order to enhance the discharge runtime and to reduce the methanol crossover.

The equivalent circuit model with optimized lumped non‐linear parameters can be used when designing power management units for portable electronic devices.

This paper gives a bibliographical review of the finite element methods (FEMs) applied to the analysis of ceramics and glass materials. The bibliography at the end of the paper contains references to papers, conference proceedings and theses/dissertations on the subject that were published between 1977‐1998. The following topics are included: ceramics – material and mechanical properties in general, ceramic coatings and joining problems, ceramic composites, ferrites, piezoceramics, ceramic tools and machining, material processing simulations, fracture mechanics and damage, applications of ceramic/composites in engineering; glass – material and mechanical properties in general, glass fiber composites, material processing simulations, fracture mechanics and damage, and applications of glasses in engineering.

To evaluate the corrosion performance and nano‐mechanical behaviour of a brass substrate covered by different thick SiO₂ layers deposited by means of plasma enhanced chemical vapour deposition (PECVD) technique.

The comparison between laboratory and “industrial” objects revealed a very good corrosion behaviour and good mechanical performance of both of them: in particular it was possible to modulate the surface treatment to solve various problems from the industrial point of view.

It was possible to reduce the Cu migration into the SiO₂ coating during the PECVD deposition at a negligible level and to control it by the deposition; further, the nano‐indentation tests revealed the great utility of the coating annealing in obtaining a significant improvement of the mechanical properties of the coated objects.

Even if some industrial problems were solved (minimization of the presence of the coating defects and transparency of the coatings), some on the layer hardness (anti‐wear behaviour of the industrial objects) has to be better investigated and possibly solved.

The work reports a deposition process that is carried out industrially over a two year period.

This research reports a PECVD process realized on industrial objects: the originality is in the reached corrosion and mechanical performances that made it possible to realize a satisfactory industrial deposition.

The purpose of this paper is to determine the corrosion fatigue behavior and mechanism of 6005A aluminum alloy and welded joint.

Electron back-scattered diffraction (EBSD) were adopted to characterize the microstructure of 6005A aluminum alloy and welded joint. Through potentiodynamic polarization, electrochemical impedance spectroscopy (EIS) and corrosion fatigue experiments, the corrosion fatigue behavior and mechanism of 6005A aluminum alloy base metal and welded joint were studied.

The results show that the corrosion fatigue crack initiation of 6005A aluminum alloy base metal and welded joint is mainly caused by the preferential anodic dissolution and hydrogen concentration in the areas with inclusions and welding defects.

The research is an originality study on the corrosion fatigue behavior and mechanism of 6005A aluminum alloy and welded joint.