650 research outputs found
Fault detection and fault-tolerant control for nonlinear systems
No full textLinlin Li addresses the analysis and design issues of observer-based FD and FTC for nonlinear systems. The author analyses the existence conditions for the nonlinear observer-based FD systems to gain a deeper insight into the construction of FD systems. Aided by the T-S fuzzy technique, she recommends different design schemes, among them the L_inf/L_2 type of FD systems. The derived FD and FTC approaches are verified by two benchmark processes. Contents Overview of FD and FTC Technology Configuration of Nonlinear Observer-Based FD Systems Design of L2 nonlinear Observer-Based FD Systems Design of Weighted Fuzzy Observer-Based FD Systems FTC Configurations for Nonlinear Systems< Application to Benchmark Processes Target Groups Researchers and students in the field of engineering with a focus on fault diagnosis and fault-tolerant control fields The Author Dr. Linlin Li completed her dissertation under the supervision of Prof. Steven X. Ding at the Faculty of Engineering, University of Duisburg-Essen, Germany
An Analytical Solution to the One-Dimensional Heat Conduction–Convection Equation in Soil
No full textSoil heat transfer occurs by conduction and convection. Soil temperatures below infiltrating water can provide a signal for water flux. In earlier work, analysis of field measurements with a sine wave model indicated that convection heat transfer made significant contributions to the subsurface temperature oscillations. In this work, we used a Fourier series to describe soil surface temperature variations with time. The conduction and convection heat transfer equation with a multi-sinusoidal wave boundary condition was solved analytically using a Fourier transformation. Soil temperature values calculated by the single sine wave model and by the Fourier series model were compared with field soil temperature values measured at depths of 0.1 and 0.3 m below an infiltrating ponded surface. The Fourier series model provided better estimates of observed field temperatures than the sine wave model. The new model provides a general way to describe soil temperature under an infiltrating water source.This article is published as Wang, Linlin, Zhiqiu Gao, Robert Horton, Donald H. Lenschow, Kai Meng, and Dan B. Jaynes. "An analytical solution to the one-dimensional heat conduction–convection equation in soil." Soil Science Society of America Journal 76, no. 6 (2012): 1978-1986. doi: 10.2136/sssaj2012.0023N. Posted with permission.</p
Examining Significant Fators of Satisfaction And Performance with Online Learning Among Graduate Students in Chengdu, China
No full textPurpose: The aim of this study is to investigate the factors that impact students' satisfaction with and effectiveness of online learning within the context of four universities closely affiliated with the Ministry of Education in Chengdu. Within this research framework, we have selected seven latent variables for in-depth analysis: perceived usefulness, perceived ease of use, perceived quality, trust, satisfaction, behavioral intention, and performance. Research design, data, and methodology: The study was executed using a quantitative survey methodology by the researchers. A comprehensive on-site questionnaire survey was administered to 500 graduate students who had previous online learning experience within four universities in Chengdu. The sampling process incorporated judgmental, stratified random, and convenience sampling methods. In terms of statistical techniques, this study made use of confirmatory factor analysis (CFA) and structural equation modeling (SEM). Results: Perceived usefulness, perceived ease of use, perceived quality, and trust exert significant influences on satisfaction. Additionally, satisfaction plays a significant role in shaping behavioral intention and performance. However, it is worth noting that perceived ease of use does not significantly impact perceived usefulness. Conclusions: Educational institutions and policymakers should take these findings into consideration when designing and implementing online learning programs
Semi-autonomous control of an unmanned aerial vehicle
No full textUnmanned Aerial Vehicle in short is UAV and it is widely recognized and known to the public. It becomes more and more importance in military and civil applications. UAV can replace human pilot but ground control or even machine control and this help to reduce the danger to the human body for different missions. Nowadays, there is a rapid increase in a number of people who take part of building their own UAV, formally known as drone or flying robot. There are two main classifications for UAV, which is semi-autonomous and fully autonomous.
The purpose of this report is to present the design and the construction detail of UAVs. In this report, both hardware and software specification will mention and how it is assembly, calibration and test. This quad-copter was able to complete the mission that had been set by the competition committees.
This quad-copter had been performing in the Singapore Amazing Flying Machine Competition 2016 and it had finished all the missions. One of the quad-copters had achieved the 2nd Best Platform Award and 3rd Championship Award in the Category D1 (Semi-Autonomous Group).Bachelor of Engineerin
Development of a novel continuum damage mechanics-based machine learning approach for vibration fatigue assessment of fastener clip subjected to high-frequency vibration
No full textThis paper proposes a novel method based on continuum damage mechanics (CDM) and machine learning (ML) models to evaluate the vibration fatigue behavior of W1-type railway fastener clips subjected to high-frequency vibration. Firstly, static and fatigue tests are conducted on 60Si2Mn spring steel to acquire elastic modulus, tensile strength, and P-S-N curves. Subsequently, a CDM model is established, and numerical simulations are performed under various working conditions to obtain the fatigue characteristics of the clips. Finally, the ML model is trained using numerical simulation results, thereby establishing a mapping model between the working conditions and fatigue characteristics. The developed ML model demonstrates high accuracy in predicting the vibration fatigue life of the clips. Moreover, the Shapley Additive Explanations (SHAP) algorithm is employed to elucidate the ML model, revealing that the vibration frequency has a greater impact on the fatigue life of the clips compared to the vibration displacement.The authors sincerely acknowledge the support from the National Natural Science Foundation of China (No. 12002011). Linlin Sun is supported by the scientific research project of China Academy of Railway Sciences Co., Ltd. (2021YJ069)
A novel hybrid technique for short-term electricity price forecasting in deregulated electricity markets
No full textThis thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Short-term electricity price forecasting is now crucial practice in deregulated electricity markets, as it forms the basis for maximizing the profits of the market participants. In this thesis, short-term electricity prices are forecast using three different predictor schemes, Artificial Neural Networks (ANNs), Support Vector Machine (SVM) and a hybrid scheme, respectively.
ANNs are the very popular and successful tools for practical forecasting. In this thesis, a hidden-layered feed-forward neural network with back-propagation has been adopted for detailed comparison with other forecasting models. SVM is a newly developed technique that has many attractive features and good performance in terms of prediction. In order to overcome the limitations of individual forecasting models, a hybrid technique that combines Fuzzy-C-Means (FCM) clustering and SVM regression algorithms is proposed to forecast the half-hour electricity prices in the UK electricity markets. According to the value of their power prices, thousands of the training data are classified by the unsupervised learning method of FCM clustering. SVM regression model is then applied to each cluster by taking advantage of the aggregated data information, which reduces the noise for each training program.
In order to demonstrate the predictive capability of the proposed model, ANNs and SVM models are presented and compared with the hybrid technique based on the same training and testing data sets in the case studies by using real electricity market data. The data was obtained upon request from APX Power UK for the year 2007.
Mean Absolute Percentage Error (MAPE) is used to analyze the forecasting errors of
different models and the results presented clearly show that the proposed hybrid
technique considerably improves the electricity price forecasting
A safety investment optimization model for power grid enterprises based on System Dynamics and Bayesian network theory
No full textIn recent years, frequent large-scale power grid accidents have caused serious economic losses and bad social impact, which has drawn great attention from power grid enterprises. As one of the key elements of production, safety investment plays an important role in improving the safety level and reducing accident loss. In this paper, System dynamics (SD) and Bayesian network (BN) are integrated to develop a novel safety investment optimization model for power grid enterprises, which takes into account the impact of safety investment factors on accidents and the interactions between them. Based on sensitivity analysis, critical safety investment factors are determined to form the subsystem of the SD model. Subsequently, the optimal safety investment strategy is determined by a three-step simulation. The simulation results show that there are barrel effects and a diminishing marginal utility in safety investment. The proposed safety investment optimization model is practical to provide technical supports and guidance for determining an effective safety investment strategy in power grid enterprises.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Safety and Security Scienc
Diagnosis of Mycobacterium marinum infection based on photochromogenicity: a case report
No full textA 35-year-old immunocompetent woman from southern China went to the hand surgery clinic with a six-month history of progressive swelling in her right index finger. She had been pinched by a lobster and had received several treatments without any improvement. Pus specimens were taken from the swollen parts of her finger, and the pathology showed granulomatous inflammation. Ziehl–Neelsen staining revealed positive bacillus in the pus specimens. The bacteria grew well on Columbia blood agar. However, the MALDI-TOF MS and 16S rRNA gene sequencing were not able to distinguish between Mycobacterium marinum and Mycobacterium ulcerans because of their close genetic relationship. Photochromogenicity testing can help differentiate between these species based on the alteration in colony color after light exposure. For our patient, the colonies turned yellow after 18h of incubation in the sun, identifying the species as M. marinum. Besides surgical drainage, the patient received rifampicin and clarithromycin for three months, and her symptoms resolved without relapse after six months of follow-up
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