Search results

The purpose of this paper is to introduce an improved system identification method for small unmanned helicopters combining adaptive ant colony optimization algorithm and Levy’s method and to solve the problem of low model prediction accuracy caused by low-frequency domain curve fitting in the small unmanned helicopter frequency domain parameter identification method.

This method uses the Levy method to obtain the initial parameters of the fitting model, uses the global optimization characteristics of the adaptive ant colony algorithm and the advantages of avoiding the “premature” phenomenon to optimize the initial parameters and finally obtains a small unmanned helicopter through computational optimization Kinetic models under lateral channel and longitudinal channel.

The algorithm is verified by flight test data. The verification results show that the established dynamic model has high identification accuracy and can accurately reflect the dynamic characteristics of small unmanned helicopter flight.

This paper presents a novel and improved frequency domain identification method for small unmanned helicopters. Compared with the conventional method, this method improves the identification accuracy and reduces the identification error.

With the popularity of high-rise buildings, wall inspection and cleaning are becoming more difficult and associated with danger. The best solution is to replace manual work with wall-climbing robots. Therefore, this paper proposes a design method for a rolling-adsorption wall-climbing robot (RWCR) based on vacuum negative pressure adsorption of the crawler. It can improve the operation efficiency while solving the safety problems.

The pulleys and tracks are used to form a dynamic sealing chamber to improve the dynamic adsorption effect and motion flexibility of the RWCR. The mapping relationship between the critical minimum adsorption force required for RWCR downward slip, longitudinal tipping and lateral overturning conditions for tipping and the wall inclination angle is calculated using the ultimate force method. The pressure and gas flow rate distribution of the negative pressure chamber under different slit heights of the negative pressure mechanism is analysed by the fluid dynamics software to derive the minimum negative pressure value that the fan needs to provide.

Simulation and test results show that the load capacity of the RWCR can reach up to 6.2 kg on the smooth glass wall, and the maximum load in the case of lateral movement is 4.2 kg, which verifies the rationality and effectiveness of the design.

This paper presents a new design method of a RWCR for different rough wall surfaces and analyses the ultimate force state and hydrodynamic characteristics.

The purpose of this study is to develop optimal evacuation plan to provide valuable theoretical and practical insight in the fire evacuation work of similar structures, by proposing a systematic simulation-based guided-evacuation agent-based model (GAM) and a three-stage mathematical evacuation model to investigate how to simulate, assess and improve the performance efficiency of the evacuation plan.

The authors first present the self-evacuation and guided-evacuation models to determine the optimal evacuation plan in ship chamber. Three key performance indicators are put forward to quantitatively assess the evacuation performance within the two fire scenarios. The evacuation model in tower is built to obtain the dividing points of the three different fire evacuation plans.

The study shows that the optimal evacuation plan determined by the GAM considering social relationships effectively relieves the congestion or collision of evacuees and improves the evacuation uniformity. The optimal evacuation plan not only solves the crush caused by congestion or collision of evacuees but also can greatly shorten the evacuation time for passenger ship fire.

This study establishes the GAM considering the interactive evacuee characteristics and the proportion of evacuees guided by the crew members to make the optimal evacuation plan more time-efficient. The self-evacuation process is simulated to assess the performance of the guided-evacuation strategies, which are used to verify the effectiveness and feasibility of the optimal evacuation plan in this research.

This study aims to show that the best-performing realized measures vary across markets when it comes to forecast real estate investment trust (REIT) volatility. This finding provides little guidance for practitioners on which one to use when facing a new market. The authors attempt to fill the hole by seeking a common estimator, which can study for different markets.

The authors do so by drawing upon the general forecasting literature, which finds that combinations of individual forecasts often outperform even the best individual forecast. The authors carry out the study by first introducing a number of commonly used realized measures and then considering several different combination strategies. The authors apply all of the individual measures and their different combinations to three major global REIT markets (Australia, UK and US).

The findings show that both unconstrained and constrained versions of the regression-based combinations consistently rank among the group of best forecasters across the three markets under study. None of their peers can do it including the three simple combinations and all of the individual measures. The conclusions are robust to the choice of evaluation metrics and of the out-of-sample evaluation periods.

The study provides practitioners with easy-to-follow insights on how to forecast REIT volatility, that is, use a regression-based combination of individual realized measures. The study has also extended the thin real estate literature on using high-frequency data to examine REIT volatility.

Visual quality control on raw textile fabrics is a vital process in weaving factories to ensure their exterior quality (visual defects or imperfection) satisfying customer requirements. Commonly, this critical process is manually conducted by human inspectors, which can hardly provide a fast and reliable inspection results due to fatigue and subjective errors. To meet modern production needs, it is highly demanded to develop an automated defect inspection system by replacing human eyes with computer vision.

As a structural texture, fabric textures can be effectively represented by a linearly summation of basic elements (dictionary). To create a robust representation of a fabric texture in an unsupervised manner, a smooth constraint is imposed on dictionary learning model. Such representation is robust to defects when using it to recover a defective image. Thus an abnormal map (likelihood of defective regions) can be computed by measuring similarity between recovered version and itself. Finally, the total variation (TV) based model is built to segment defects on the abnormal map.

Different from traditional dictionary learning method, a smooth constraint is introduced in dictionary learning that not only able to create a robust representation for fabric textures but also avoid the selection of dictionary size. In addition, a TV based model is designed according to defects' characteristics. The experimental results demonstrate that (1) the dictionary with smooth constraint can generate a more robust representation of fabric textures compared to traditional dictionary; (2) the TV based model can achieve a robust and good segmentation result.

The major originality of the proposed method are: (1) Dictionary size can be set as a constant instead of selecting it empirically; (2) The total variation based model is built, which can enhance less salient defects, improving segmentation performance significantly.

Establishing and developing digital science and education evaluation platforms (DSEEPs) have several practical implications for the development of China's science, technology and education. Identifying and analyzing the key factors influencing DSEEP user experience (UX) can improve the users' willingness to use the platform and effectively promote its sustainable development.

First, a literature survey, a five-element model of UX and semi-structured interviews were used in this study to develop a DSEEP UX-influencing factor model, which included five dimensions and 22 influencing factors. Second, the model validity was verified using questionnaire data. Finally, the key influencing factors were identified and analyzed using a fuzzy decision-making trial and evaluation laboratory (fuzzy-DEMATEL) method.

Fourteen influencing factors, including diverse information forms and comprehensive information content, are crucial for the DSEEP UX. Its optimization path is “‘Function Services’ → ‘Information Resources’ → ‘Interaction Design’ → ‘Interface Design’ and ‘Visual Design’.” In this regard, platform managers can take the following measures to optimize UX: strengthening functional services, improving information resources, enhancing the interactive experience and considering interface effects.

This study uses a combination of qualitative and quantitative research methods to determine the key influencing factors and optimization path of DSEEP UX. Optimization suggestions for UX are proposed from the perspective of platform managers, who provide an effective theoretical reference for innovating and developing a DSEEP.

Cutting force prediction is pretty important for manufacture management. Thus, the purpose of this paper is to obtain the cutting force of the machining process with high efficiency and low cost. A method based on the improved auto regressive moving average (ARMA) model is proposed for cutting force predictions in milling process.

First, classification and normalization are made for initial cutting force. Second, the cutting force sequences are compressed followed singular and valid value removed. At last, the improved ARMA model is used for cutting force fit and extrapolation considered the time domain characteristics.

A series of cutting force with the spindle speed 595r/min is carried out in the research. It is showed that the mean absolute percentage error value of cutting force extrapolation results which is based on the improved model is smaller. The percentage value is approximately 5.80%. Then the root mean square error test value is only 72.49, which is smaller than that with other traditional method, such as hidden Markov model. The extrapolation results with the proposed model performed good consistency and accuracy in terms of peaks, valleys and volatility compared with the experiment results.

The proposed method that is based on the improved ARMA model can be used for cutting force predictions conveniently. And the predictions can be used for improving the qualities in milling process.

The purpose of this paper is to evaluate the properties of several thiol-acrylate photosensitive systems and compare with corresponding acrylate free-radical systems. The potential stereolithography applications of thiol–ene photosensitive systems are also discussed.

In the both thiol–ene and acrylate free-radical photosensitive systems, various key performances were characterized. The function group conversions were characterized by real-time Fourier transform infrared spectroscopy. The tension strength was determined according to the standard ASTM D638-2003, the flexible strength was determined according to ASTM D790-07 and the hardness was measured according to ASTM D2240-05. The volume shrinkage was measured by dilatometer method. The glass transition temperature was analyzed by differential scanning calorimeter.

As adding mercapto propionates into acrylate system, the inhibition of polymerization by oxygen was controlled and the flexible performance was improved. In addition, the photosensitive resin showed better tension strength, higher elongation at break and lower volume shrinkage. Among the four mercapto propionates, rigid TEMPIC showed most obvious affect, followed hexa-functional DPMP, tetra-functional PETMP and tri-functional TMMP.

Although the thiol–ene photosensitive resin has unmatched advantages in performance, there are no reports on the thiol–ene photosensitive resin in the stereolithography application. In this study, thiol–ene photopolymerization material was first tentatively implemented in stereolithography area. Several critical performance parameters were compared between thiol–ene and acrylate free-radical photosensitive systems.

The purpose of this paper is to discuss an adaptive SLA mechanism for service sharing in virtual environment, which can organize and govern QoS items in terms of service execution time, reliability, and availability, and provides a common understanding about services, responsibilities, priorities, guarantees and warranties-related virtual cooperative issues.

The management framework for SLA is introduced, based on which the whole process including SLA contract, adaptive SLA negotiation strategy, SLA deployment and SLA assessment are discussed, and the prototype is implemented in the cloud manufacturing platform.

A proposed SLA framework for service sharing in virtual environments is given; electronic contracts are designed in the framework for encapsulating measurable aspects of service level agreements so as to provide common understanding about the service; and an improved SLA negotiation strategy with three phases is presented for the dynamicity of the virtual services.

The paper presents a very useful adaptive SLA mechanism for service sharing in virtual environments that can be utilized in concurrent or future advanced manufacturing modes.

This paper aims to focus on an assessment of the electrochemical corrosion performance of bulk NC copper in a variety of corrosion environments.

The electrochemical corrosion behavior of bulk nanocrystalline (NC) copper prepared by inert gas condensation and in situ warm compress technique was studied by using potentiodynamic polarization and electrochemical impedance spectroscopy tests in de-aerated 0.1 M NaOH solution.

NC copper exhibited a typical active-passive-transpassive behavior with the formation of duplex passive films, which was qualitatively similar to coarse-grain (CG) copper. Although a compact passive film formed on NC copper surface, the corrosion resistance of NC copper was lower in comparison with CG copper. The increase in corrosion rate for NC copper was mainly attributed to the high activity of surface atoms and intergranular atoms. These atoms led to an enhancement of passive ability and an increase of dissolution rate of passive film in oxygen-deficiency solution. For NC copper, the corrosion resistance decreased as grain size increased in NC range.

The difference in corrosion resistance between bulk NC copper and its CG counterpart is dependent upon the corrosion solution. In a previous work, the potentiodynamic polarization tests revealed that NC copper bulks (grain size 48, 68, 92 nm) had identical corrosion resistance to CG copper bulk in naturally aerated 0.1 M NaOH solution. The results might be related to the dissolved oxygen in the medium.