scholarly journals A Synthetic Condition Assessment Model for Power Transformers Using the Fuzzy Evidence Fusion Method

Energies ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 857 ◽  
Author(s):  
Fenglan Tian ◽  
Zhongzhao Jing ◽  
Huan Zhao ◽  
Enze Zhang ◽  
Jiefeng Liu
Keyword(s):  
Condition Assessment ◽  
Assessment Model ◽  
Condition Based Maintenance ◽  
Power Transformers ◽  
Main Body ◽  
Fusion Method ◽  
Proposed Model ◽  
Electric Enterprises ◽  
Grade Division ◽  
Financial Losses

Condition-based maintenance decision-making of transformers is essential to electric enterprises for avoiding financial losses. However, precise transformer condition assessment was tough to accomplish because of the negligence of the influence of bushing and accessories, the difficulty of fuzzy grade division, and the lack of reasonable fuzzy evidence fusion method. To solve these problems, a transformer assessing model was proposed in the paper. At first, an index assessing system, considering the main body, the bushing and the accessories components, was established on the basis of components division of transformers. Then, a Cauchy membership function was employed for fuzzy grades division. Finally, a fuzzy evidence fusion method was represented to handle the fuzzy evidences fusion processes. Case studies and the comparison analysis with other methods were performed to prove the effectiveness of this model. The research results confirm that the proposed model could be recommendation for condition based maintenance of power transformers for electric enterprises.

Higher-Order Thinking Skills (HOTS)-based Formative Assessment: A Proposed Model for Language Learning Assessment

2020 ◽  
Vol 9 (2) ◽  
pp. 115
Author(s):  
Wiyaka Wiyaka ◽  
Entika Fani Prastikawati ◽  
AB Prabowo Kusumo Adi
Keyword(s):  
Formative Assessment ◽  
Language Learning ◽  
Higher Order Thinking ◽  
Thinking Skills ◽  
Higher Order ◽  
Formative Assessments ◽  
Assessment Model ◽  
Higher Order Thinking Skills ◽  
Learning Assessments ◽  
Proposed Model

<div><p class="StyleABSTRAKenCambria">The integration of higher-order thinking skills (HOTS) in language learning assessments has become a crucial issue in 21st-century learning. However, not many teachers are aware of the need to incorporate HOTS in assessments due to their insufficient knowledge and the absence of good examples. Further, there is not much research and literature on HOTS-based formative assessment that can be used as references. This research aims to fill the existing gap by providing a model of higher-order thinking skills (HOTS)-based formative assessments for English learning, especially in junior high schools. By employing research and development design, this research describes the validation of the assessment model. The proposed model of assessment may be used as a prototype for assessing language learning.</p></div><p> </p>

Power Transformer Fault Diagnosis Based on Vibration Correlation Analysis

2014 ◽  
Author(s):  
Kaixing Hong ◽  
Hai Huang
Keyword(s):  
Fault Diagnosis ◽  
Correlation Analysis ◽  
Fundamental Frequency ◽  
Vibration Analysis ◽  
Laboratory Tests ◽  
Power Transformer ◽  
Assessment Model ◽  
Vibration Method ◽  
Proposed Model ◽  
Transformer Fault

In this paper, a condition assessment model using vibration method is presented to diagnose winding structure conditions. The principle of the model is based on the vibration correlation. In the model, the fundamental frequency vibration analysis is used to separate the winding vibration from the tank vibration. Then, a health parameter is proposed through the vibration correlation analysis. During the laboratory tests, the model is validated on a test transformer, and manmade deformations are provoked in a special winding to compare the vibrations under different conditions. The results show that the proposed model has the ability to assess winding conditions.

scholarly journals PROPOSING A NEW METHODOLOGY BASED ON FUZZY LOGIC FOR TUNNELLING RISK ASSESSMENT

2014 ◽  
Vol 20 (1) ◽  
pp. 82-94 ◽  
Author(s):  
Abdolreza Yazdani-Chamzini
Keyword(s):  
Risk Assessment ◽  
Fuzzy Inference ◽  
Assessment Model ◽  
Tunnel Construction ◽  
Construction Operations ◽  
Protective Measures ◽  
Inference System ◽  
Proposed Model ◽  
Mine Development ◽  
Civil Defence

Tunnels are artificial underground spaces that provide a capacity for particular goals such as storage, under-ground transportation, mine development, power and water treatment plants, civil defence. This shows that the tunnel construction is a key activity in developing infrastructure projects. In many situations, tunnelling projects find themselves involved in the situations where unexpected conditions threaten the continuity of the project. Such situations can arise from the prior knowledge limited by the underground unknown conditions. Therefore, a risk analysis that can take into account the uncertainties associated with the underground projects is needed to assess the existing risks and prioritize them for further protective measures and decisions in order to reduce, mitigate and/or even eliminate the risks involved in the project. For this reason, this paper proposes a risk assessment model based on the concepts of fuzzy set theory to evaluate risk events during the tunnel construction operations. To show the effectiveness of the proposed model, the results of the model are compared with those of the conventional risk assessment. The results demonstrate that the fuzzy inference system has a great potential to accurately model such problems.

Condition assessment of power transformers based on multi-attributes using fuzzy logic

2017 ◽  
Vol 11 (8) ◽  
pp. 983-990 ◽  
Author(s):  
Chilaka Ranga ◽  
Ashwani Kumar Chandel ◽  
Rajeevan Chandel
Keyword(s):  
Fuzzy Logic ◽  
Condition Assessment ◽  
Power Transformers

scholarly journals Modified Decision Tree Technique for Ransomware Detection at Runtime through API Calls

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Faizan Ullah ◽  
Qaisar Javaid ◽  
Abdu Salam ◽  
Masood Ahmad ◽  
Nadeem Sarwar ◽  
...  
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Decision Tree ◽  
Feature Vector ◽  
Machine Learning Algorithms ◽  
The Novel ◽  
Proposed Model ◽  
Testing Accuracy ◽  
Financial Losses

Ransomware (RW) is a distinctive variety of malware that encrypts the files or locks the user’s system by keeping and taking their files hostage, which leads to huge financial losses to users. In this article, we propose a new model that extracts the novel features from the RW dataset and performs classification of the RW and benign files. The proposed model can detect a large number of RW from various families at runtime and scan the network, registry activities, and file system throughout the execution. API-call series was reutilized to represent the behavior-based features of RW. The technique extracts fourteen-feature vector at runtime and analyzes it by applying online machine learning algorithms to predict the RW. To validate the effectiveness and scalability, we test 78550 recent malign and benign RW and compare with the random forest and AdaBoost, and the testing accuracy is extended at 99.56%.

scholarly journals Quantifying the Environmental and Economic Performance of Remote Communities

2019 ◽  
Vol 8 (4) ◽  
pp. 176 ◽  
Author(s):  
Jamie Filer ◽  
Steven Schuldt
Keyword(s):  
Management Practices ◽  
Sustainability Assessment ◽  
Assessment Model ◽  
Remote Site ◽  
Construction Costs ◽  
Remote Communities ◽  
Renewable Energy Systems ◽  
Proposed Model ◽  
Waste Management Practices ◽  
Post Disaster

Remote communities such as oil production sites, post-disaster housing camps, and military forwardoperating bases (FOB) are often detached from established infrastructure grids, requiring a constantresupply of resources. In one instance, a 600-person FOB required 22 trucks per day to delivernecessary fuel and water and remove generated wastes. This logistical burden produces negativeenvironmental impacts and increases operational costs. To minimize these consequences,construction planners can implement sustainability measures such as renewable energy systems,improved waste management practices, and energy-efficient equipment. However, integration ofsuch upgrades can increase construction costs, presenting the need for a tool that identifies tradeoffsamong conflicting criteria. To assist planners in these efforts, this paper presents the development ofa novel remote site sustainability assessment model capable of quantifying the environmental andeconomic performance of a set of infrastructure alternatives. Through field data and literatureestimates, a hypothetical FOB is designed and evaluated to demonstrate the model’s distinctivecapability to accurately and efficiently assess construction alternatives. The proposed model willenable construction planners to maximize the sustainability of remote communities, creating sitesthat are more self-sufficient with reduced environmental impacts.Keywords: Sustainability, infrastructure, remote communities

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