A case study of industrial data analysis: Gearbox temperature prediction of wind turbines using ensemble deep learning regression

2021 ◽  
Author(s):  
Zhiwei Cheng ◽  
Yongsheng Deng ◽  
Xiaodan Wang ◽  
Zhihong Xie
Keyword(s):  
Deep Learning ◽  
Data Analysis ◽  
Wind Turbines ◽  
Temperature Prediction ◽  
Industrial Data

Teaching Computer Based Historical Data Analysis

1994 ◽  
Vol 6 (1) ◽  
pp. 52-58 ◽  
Author(s):  
Charles Anderson ◽  
Robert J. Morris
Keyword(s):  
Data Analysis ◽  
Social History ◽  
Historical Data ◽  
Good Practice ◽  
Computer Assisted ◽  
Historical Data Analysis ◽  
University Of Edinburgh ◽  
Computer Based ◽  
The University

A case study ofa third year course in the Department of Economic and Social History in the University of Edinburgh isusedto considerandhighlightaspects of good practice in the teaching of computer-assisted historical data analysis.

KAJIAN PENYELENGGARAAN PAUD DI KOTA BANJARMASIN DITINJAU DARI ASPEK PERENCANAAN

2018 ◽  
Vol 2 (2) ◽  
pp. 159
Author(s):  
Lisna Sulinar Sari
Keyword(s):  
Early Childhood ◽  
Data Analysis ◽  
Early Childhood Education ◽  
Educational Needs ◽  
Needs Analysis ◽  
Case Study Approach ◽  
Childhood Education ◽  
Study Approach ◽  
Early Childhood Institutions

Abstrak: Permasalahan dalam penelitian ini yaitu dari jumlah lembaga PAUD yang ada diKota Banjarmasin belum semuanya memiliki perencanaan khususnya pada analisispeningkatan legalitas kelembagaan PAUD dan analisis kebutuhan pendidikan untuk anak usiadini (AUD). Penelitian ini menggunakan pendekatan studi kasus dengan analisis data deskrtifkuantitatif dan kualitataif. Hasil studi menunjukkan bahwa: i) Disdik Kota Banjarmasin danLembaga PAUD sampel tidak melakukan perencanaan yang baik untuk pendataan analisiskebutuhan pendidikan AUD; ii) Belum semua lembaga PAUD sampel memiliki izinoperasional dikarenakan adanya persyaratan yang belum dapat dipenuhi karena memerlukanbiaya yang cukup besar seperti, pembuatan akta notaris; iii) Belum semua lembaga PAUDmemiliki sarpras sesuai dengan pedoman sarana dan prasarana dari pusat; iv) untuk membantuketersediaan sarpras, Disdik Kota Banjarmasin sudah mengalokasikan dana APBD II berupabantuan RKB, rehab kelas rusak ringan dan berat, serta bantuan APE Dalam dan Luar berupabarang. Abstract: The problem in this study is from the number of early childhood institutions in thecity of Banjarmasin not all have plans in particular to the analysis of institutional legalityincrease early childhood education and educational needs analysis for early childhood (AUD).This study uses a case study approach to data analysis of quantitative and qualitative deskrtif.The study shows that: i) Disdik Banjarmasin and Institutions ECD sample is not doing betterplanning for data analysis AUD educational needs; ii) Not all the samples of early childhoodinstitutions have an operating permit because of the requirements can not be met because itrequires significant costs such as notary deed; iii) Not all early childhood institutions haveinfrastructure accordance with the guidelines of the central infrastructure; iv) to assist theavailability infrastructure, Disdik Banjarmasin already allocated budget II in the form ofclassroom assistance, rehabilitation of damaged light and heavy classes, as well as the In andOut APE assistance in the form of goods.

scholarly journals Offshore Wind Energy Resource Assessment across the Territory of Oman: A Spatial-Temporal Data Analysis

2021 ◽  
Vol 13 (5) ◽  
pp. 2862
Author(s):  
Amer Al-Hinai ◽  
Yassine Charabi ◽  
Seyed H. Aghay Kaboli
Keyword(s):  
Data Analysis ◽  
Wind Energy ◽  
Wind Turbines ◽  
Energy Resource ◽  
Wind Farms ◽  
Offshore Wind ◽  
Wind Data ◽  
Offshore Wind Energy ◽  
Offshore Wind Turbines ◽  
Wind Potential

Despite the long shoreline of Oman, the wind energy industry is still confined to onshore due to the lack of knowledge about offshore wind potential. A spatial-temporal wind data analysis is performed in this research to find the locations in Oman’s territorial seas with the highest potential for offshore wind energy. Thus, wind data are statistically analyzed for assessing wind characteristics. Statistical analysis of wind data include the wind power density, and Weibull scale and shape factors. In addition, there is an estimation of the possible energy production and capacity factor by three commercial offshore wind turbines suitable for 80 up to a 110 m hub height. The findings show that offshore wind turbines can produce at least 1.34 times more energy than land-based and nearshore wind turbines. Additionally, offshore wind turbines generate more power in the Omani peak electricity demand during the summer. Thus, offshore wind turbines have great advantages over land-based wind turbines in Oman. Overall, this work provides guidance on the deployment and production of offshore wind energy in Oman. A thorough study using bankable wind data along with various logistical considerations would still be required to turn offshore wind potential into real wind farms in Oman.

scholarly journals An Evaluation of the Formative Experiences of Students Enrolled in Postgraduate Studies in Education: Case Study in Northern Mexico

2021 ◽  
Vol 13 (9) ◽  
pp. 4790
Author(s):  
Brenda Imelda Boroel Cervantes ◽  
José Alfonso Jiménez Moreno ◽  
Salvador Ponce Ceballos ◽  
José Sánchez Santamaría
Keyword(s):  
Data Analysis ◽  
Focus Groups ◽  
Teaching Staff ◽  
Training Context ◽  
Northern Mexico ◽  
Postgraduate Studies ◽  
Successful Design ◽  
Formative Experiences

The educational journey in postgraduate programs is linked to the actors, processes and results, setting the tone for different approaches from the perspective of characterization, development and evaluation. It is summarized in a sequential manner in four stages: entry to the program, progress within the program, and the final educational stretch, where the instructor/tutor plays an important part and obtaining the diploma or degree. The goal of this research was to evaluate, using the students’ perceptions, formative experiences as a result of their academic journey in postgraduate programs within education in Northern Mexico. We have used a case study based on the focus groups technique, applied to a sample of cases comprised of students enrolled in their final educational stage. The information was analyzed using inductive data analysis. The main results were grouped into three meta categories: (1) development of professional skills for the successful design of the intervention proposal, which unfolded into four categories; (2) the role of the tutor during the formative process, consisting of four analysis categories and (3) contributions of the teaching staff in their profession, consisting of two categories. These trends also evidence the formative abundance in the personal, academic and social training context of the students.

Deep learning and complex network theory based analysis on socialized manufacturing resources utilisations and an application case study

2021 ◽  
pp. 1063293X2110031
Author(s):  
Maolin Yang ◽  
Auwal H Abubakar ◽  
Pingyu Jiang
Keyword(s):  
Deep Learning ◽  
Complex Network ◽  
Network Models ◽  
Neural Network Models ◽  
Complex Network Theory ◽  
New Type ◽  
Manufacturing Resource ◽  
Manufacturing Resources ◽  
Resource Characteristics

Social manufacturing is characterized by its capability of utilizing socialized manufacturing resources to achieve value adding. Recently, a new type of social manufacturing pattern emerges and shows potential for core factories to improve their limited manufacturing capabilities by utilizing the resources from outside socialized manufacturing resource communities. However, the core factories need to analyze the resource characteristics of the socialized resource communities before making operation plans, and this is challenging due to the unaffiliated and self-driven characteristics of the resource providers in socialized resource communities. In this paper, a deep learning and complex network based approach is established to address this challenge by using socialized designer community for demonstration. Firstly, convolutional neural network models are trained to identify the design resource characteristics of each socialized designer in designer community according to the interaction texts posted by the socialized designer on internet platforms. During the process, an iterative dataset labelling method is established to reduce the time cost for training set labelling. Secondly, complex networks are used to model the design resource characteristics of the community according to the resource characteristics of all the socialized designers in the community. Two real communities from RepRap 3D printer project are used as case study.

scholarly journals A Computer Vision-Based Occupancy and Equipment Usage Detection Approach for Reducing Building Energy Demand

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 156
Author(s):  
Paige Wenbin Tien ◽  
Shuangyu Wei ◽  
John Calautit
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Energy Demand ◽  
Energy Savings ◽  
Internal Heat ◽  
Electrical Equipment ◽  
Building Energy ◽  
Hvac Systems ◽  
Equipment Usage

Because of extensive variations in occupancy patterns around office space environments and their use of electrical equipment, accurate occupants’ behaviour detection is valuable for reducing the building energy demand and carbon emissions. Using the collected occupancy information, building energy management system can automatically adjust the operation of heating, ventilation and air-conditioning (HVAC) systems to meet the actual demands in different conditioned spaces in real-time. Existing and commonly used ‘fixed’ schedules for HVAC systems are not sufficient and cannot adjust based on the dynamic changes in building environments. This study proposes a vision-based occupancy and equipment usage detection method based on deep learning for demand-driven control systems. A model based on region-based convolutional neural network (R-CNN) was developed, trained and deployed to a camera for real-time detection of occupancy activities and equipment usage. Experiments tests within a case study office room suggested an overall accuracy of 97.32% and 80.80%. In order to predict the energy savings that can be attained using the proposed approach, the case study building was simulated. The simulation results revealed that the heat gains could be over or under predicted when using static or fixed profiles. Based on the set conditions, the equipment and occupancy gains were 65.75% and 32.74% lower when using the deep learning approach. Overall, the study showed the capabilities of the proposed approach in detecting and recognising multiple occupants’ activities and equipment usage and providing an alternative to estimate the internal heat emissions.

scholarly journals Impact of Typhoons on Floating Offshore Wind Turbines: A Case Study of Typhoon Mangkhut

2021 ◽  
Vol 9 (5) ◽  
pp. 543
Author(s):  
Jiawen Li ◽  
Jingyu Bian ◽  
Yuxiang Ma ◽  
Yichen Jiang
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Safety Evaluation ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Motion Response ◽  
Offshore Wind Turbines ◽  
Floating Offshore Wind Turbines ◽  
Coupling Motion

A typhoon is a restrictive factor in the development of floating wind power in China. However, the influences of multistage typhoon wind and waves on offshore wind turbines have not yet been studied. Based on Typhoon Mangkhut, in this study, the characteristics of the motion response and structural loads of an offshore wind turbine are investigated during the travel process. For this purpose, a framework is established and verified for investigating the typhoon-induced effects of offshore wind turbines, including a multistage typhoon wave field and a coupled dynamic model of offshore wind turbines. On this basis, the motion response and structural loads of different stages are calculated and analyzed systematically. The results show that the maximum response does not exactly correspond to the maximum wave or wind stage. Considering only the maximum wave height or wind speed may underestimate the motion response during the traveling process of the typhoon, which has problems in guiding the anti-typhoon design of offshore wind turbines. In addition, the coupling motion between the floating foundation and turbine should be considered in the safety evaluation of the floating offshore wind turbine under typhoon conditions.

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