Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Publication
- Publication Type
Articles 1 - 5 of 5
Full-Text Articles in Engineering
Sundown: Model-Driven Per-Panel Solar Anomaly Detection For Residential Arrays, Menghong Feng
Sundown: Model-Driven Per-Panel Solar Anomaly Detection For Residential Arrays, Menghong Feng
Masters Theses
There has been significant growth in both utility-scale and residential-scale solar installa- tions in recent years, driven by rapid technology improvements and falling prices. Unlike utility-scale solar farms that are professionally managed and maintained, smaller residential- scale installations often lack sensing and instrumentation for performance monitoring and fault detection. As a result, faults may go undetected for long periods of time, resulting in generation and revenue losses for the homeowner. In this thesis, we present SunDown, a sensorless approach designed to detect per-panel faults in residential solar arrays. SunDown does not require any new sensors for its fault detection and …
Structural Health Monitoring Of Pipelines In Radioactive Environments Through Acoustic Sensing And Machine Learning, Michael Thompson
Structural Health Monitoring Of Pipelines In Radioactive Environments Through Acoustic Sensing And Machine Learning, Michael Thompson
FIU Electronic Theses and Dissertations
Structural health monitoring (SHM) comprises multiple methodologies for the detection and characterization of stress, damage, and aberrations in engineering structures and equipment. Although, standard commercial engineering operations may freely adopt new technology into everyday operations, the nuclear industry is slowed down by tight governmental regulations and extremely harsh environments. This work aims to investigate and evaluate different sensor systems for real-time structural health monitoring of piping systems and develop a novel machine learning model to detect anomalies from the sensor data. The novelty of the current work lies in the development of an LSTM-autoencoder neural network to automate anomaly detection …
Machine Learning In Manufacturing: Review, Synthesis, And Theoretical Framework, Ajit Sharma, Zhibo Zhang, Rahul Rai
Machine Learning In Manufacturing: Review, Synthesis, And Theoretical Framework, Ajit Sharma, Zhibo Zhang, Rahul Rai
Business Administration Faculty Research Publications
There has been a paradigmatic shift in manufacturing as computing has transitioned from the programmable to the cognitive computing era. In this paper we present a theoretical framework for understanding this paradigmatic shift in manufacturing and the fast evolving role of artificial intelligence. Policy, Strategic and Operational implications are discussed. Implications for the future of strategy and operations in manufacturing are also discussed. Future research directions are presented.
Cnn-Based Estimation Of Sagittal Plane Walking And Running Biomechanics From Measured And Simulated Inertial Sensor Data, Eva Dorschky, Marlies Nitschke, Christine F. Martindale, Antonie J. Van Den Bogert, Anne D. Koelewijn, Bjoern M. Eskofier
Cnn-Based Estimation Of Sagittal Plane Walking And Running Biomechanics From Measured And Simulated Inertial Sensor Data, Eva Dorschky, Marlies Nitschke, Christine F. Martindale, Antonie J. Van Den Bogert, Anne D. Koelewijn, Bjoern M. Eskofier
Mechanical Engineering Faculty Publications
Machine learning is a promising approach to evaluate human movement based on wearable sensor data. A representative dataset for training data-driven models is crucial to ensure that the model generalizes well to unseen data. However, the acquisition of sufficient data is time-consuming and often infeasible. We present a method to create realistic inertial sensor data with corresponding biomechanical variables by 2D walking and running simulations. We augmented a measured inertial sensor dataset with simulated data for the training of convolutional neural networks to estimate sagittal plane joint angles, joint moments, and ground reaction forces (GRFs) of walking and running. When …
Artificial Intelligence In Plasma Electrolytic Micro-Oxidation For Surface Hardening - Insights From Scholarly Citation Networks And Patents., Priya Jadhav, Dr.Arun Bongale, Dr.Satish Kumar, Dr.Amit Kumar Tiwari
Artificial Intelligence In Plasma Electrolytic Micro-Oxidation For Surface Hardening - Insights From Scholarly Citation Networks And Patents., Priya Jadhav, Dr.Arun Bongale, Dr.Satish Kumar, Dr.Amit Kumar Tiwari
Library Philosophy and Practice (e-journal)
Objective - The purpose of this article is to analyze the top work areas and patent domains in the field of surface hardening by micro-arc oxidation. Also, it is directed on the opportunities of data analysis by different machine learning tools. Material and methods - The www.lens.org database is used to collect articles from Elsevier, Trans tech publications, Springer New York, MDPI, etc. to review the relevant articles as well as patents related to the topic. The result - A total of 1057 articles were published in 60 different journals and 756 patents in the area of research under various …