In recent years, the continuous development of machine vision technology and manipulator control technology has provided people with fast and efficient services in many fields. In some harsh environments, the manipula...
详细信息
Global sensitivity analysis (GSA) of distribution system with respect to stochastic PV and load variations plays an important role in designing optimal voltage control schemes. This paper proposes a data-driven framew...
详细信息
Global sensitivity analysis (GSA) of distribution system with respect to stochastic PV and load variations plays an important role in designing optimal voltage control schemes. This paper proposes a data-driven framework for GSA of distribution system. In particular, two representative surrogate modeling-based approaches are developed, including the traditional Gaussian process-based and the analysis of variance (ANOVA) kernel ones. The key idea is to develop a surrogate model that captures the hidden global relationship between voltage and real and reactive power injections from the historical data. With the surrogate model, the Sobol indices can be conveniently calculated through either the sampling-based method or the analytical method to assess the global sensitivity of voltage to variations of load and PV power injections. The sampling-based method estimates the Sobol indices using Monte Carlo simulations while the analytical method calculates them by resorting to the ANOVA expansion framework. Comparison results with other model-based GSA methods on the unbalanced three-phase IEEE 37-bus and 123-bus distribution systems show that the proposed framework can achieve much higher computational efficiency with negligible loss of accuracy. The results on a real 240-bus distribution system using actual smart meter data further validate the feasibility and scalability of the proposed framework.
Markov processanalysis is a dynamic modeling approach, which considers that when the current state of the system is known, the transformation development of a future state is independent of its past state. The Markov...
详细信息
ISBN:
(数字)9798350361445
ISBN:
(纸本)9798350361452
Markov processanalysis is a dynamic modeling approach, which considers that when the current state of the system is known, the transformation development of a future state is independent of its past state. The Markov process is used to model the system and the Laplace transform is used to solve the reliability indexes such as availability and reliability of the system, the Markov model can clearly represent the transformation relationship between the system states, which can fully characterize the operational capability of the system, which is of theoretical and practical significance for the reliability analysis and calculation of repairable control systems widely existed in engineering.
This paper presents a comprehensive model of an industrial electric arc furnace (EAF) that is based upon several rigorous first-principles submodels of the heat exchange in the EAF and practical experience from an ind...
详细信息
This paper presents a comprehensive model of an industrial electric arc furnace (EAF) that is based upon several rigorous first-principles submodels of the heat exchange in the EAF and practical experience from an industrial melt shop. The model is suited for process simulation, optimization, and control applications. It assumes that the energy demand of the process is satisfied by six sources, the electric arc, the oxy-fuel burners, the oxygen lances, the combustion of coal, and the oxidation of metal in the liquid and in the solid phase. The energy exchange between the liquid and the solid phase due to liquid metal splashing is also considered. The different mechanisms of heat exchange are represented in the model as follows: (a) the radiative heat exchange from the arc to the other phases is computed using the DC circuit analogy, where the view factors are calculated using exact formulae and Monte-Carlo algorithms. (b) The energy input from the oxy-fuel burner is modeled using simplified geometries for which heat transfer relationships are known. (c) The amount of heat released by the oxidation of solid metal is described by the quadratic corrosion formula. (d) The energy exchange from the bath to the solid phase due to splashing is modeled using relationships and experimental data that are available in the literature. The model contains the melting rates and the efficiency of the oxygen lancing as free parameters;their values were computed by a least squares fit to processdata of an industrial Ultra-High-Power EAF. In comparison with existing EAF models, the model presented here describes the dynamic behavior of the melting process more realistically. Based on the model, time-dependent energy efficiency curves for the various contributions and for the overall process are computed and discussed.
The proceedings contain 52 papers. The special focus in this conference is on Advanced Intelligent Technologies. The topics include: International Competitive Landscape for Generative Artificial Intelligence Technolog...
ISBN:
(纸本)9789819732098
The proceedings contain 52 papers. The special focus in this conference is on Advanced Intelligent Technologies. The topics include: International Competitive Landscape for Generative Artificial Intelligence Technology Based on Patent Metrics;A Study on Mobile Robot Path Planning in Constrained Environments Using an Enhanced RRT Algorithm;a Machine-Learning Approach in Assessing the Fama French Three and Fama French Five Factor Model;Deep Learning CNN-Based Architecture Applied to Intelligent Near-Infrared analysis of Water Pollution from Agricultural Irrigation Resources;research on the Application of Digital Twin Model Calculation and Updating Methods in Mining Engineering;research on the Factors Influencing the Horizontal Force of Body Block in the Impact Test of Steering Mechanism Based on Orthogonal Test;design and analysis of Double Arm Robot for Plate Installation;research on Public Opinion Monitoring System Based on Improved Fuzzy controller;context Understanding and Response Algorithm of Chat Robot Based on Enhanced Seq2seq Model;lane Departure Detection and Early Warning System for Intelligent Vehicles Based on Yolov3 Algorithm;attack Surface modeling Study of Printing System;non-invasive Sleep Posture analysis and Anomaly Detection Algorithm Based on Computer Vision;design of Intelligent data Synchronization and analysis Algorithm Combining Digital Twinning and Internet of Things;misalignment Detection Algorithm for Vertical Rigid Tank Channel Joints Based on Improved Yolov8n;Research on the Influential Factors of Accuracy Improvement in aPLI Dynamic Calibration;joint Audio Captioning Transformer and Stable Diffusion for Audio-to-Image Generation;research on the Design Strategy of Intelligent Rehabilitation Products Suitable for Ageing Based on Analytic Hierarchy process.
In the premium vehicle category, real-time online internet connection has become a standard in recent years. This trend is likely to spread completely in the automotive industry in the coming years. This fact offers a...
详细信息
ISBN:
(纸本)9783031152115;9783031152108
In the premium vehicle category, real-time online internet connection has become a standard in recent years. This trend is likely to spread completely in the automotive industry in the coming years. This fact offers a lot of new options in the field of vehicle maintenance (and predictive maintenance). Another possible use case may be remote diagnostics of in-use vehicles on the market, analysis of their online data and thereby an extension of the product development process after SOP. An additional new option may be to automatically collect, evaluate and generate of onboard diagnostics data to report to different authorities. E.g. OBFCM (onboard fuel consumption) or IUMPR j3 (in use monitoring performance ratio) field reports. In vehicle production, during the test drive, it could be possible to read and log of measurement data of the finished vehicle's control units online Another application may be to test vehicles online during the production process e.g. to read of DTC's (diagnostics trouble codes) during technical tests or to monitor of SoC (state of charge) of battery online while moving vehicles within the factory.
The prediction of the occupancy in buildings is essential to design efficient energy control strategies that optimize consumption and reduce losses while guaranteeing the comfort of the occupants. For this reason, man...
详细信息
The prediction of the occupancy in buildings is essential to design efficient energy control strategies that optimize consumption and reduce losses while guaranteeing the comfort of the occupants. For this reason, many works address the problem of detecting, estimating, and predicting buildings' occupancy using different techniques, devices, and technologies. The occupancy prediction process can be described in four stages: data acquisition, modeling, evaluation, and testing, which are closely related. This paper reviews the most relevant recent literature on building occupancy estimation and prediction, analyzing the key aspects of its stages. A detailed description of the variables and design considerations is presented, including measurement methods, sensor selection, modeling techniques, evaluation metrics, and different applications. Through its examination, this paper elaborates significant remarks on the interaction between the stages, providing an overview of the suitable design of the occupancy prediction process. Finally, current and future trends are discussed.
Anomaly detection is an imperative problem associated with emerging fields such as the Internet of Things, Telecommunication and Manufacturing Industries. Timely detection of anomalies and attribution to its sources e...
详细信息
ISBN:
(纸本)9781665465076
Anomaly detection is an imperative problem associated with emerging fields such as the Internet of Things, Telecommunication and Manufacturing Industries. Timely detection of anomalies and attribution to its sources enables to enforce preventive measures so as to maintain optimal process operation and avoid undesirable down-times. In this work, we propose an unsupervised method which enables detection, quantification and diagnosis of amplitude anomalies from multivariate data. The proposed method utilizes the ideas of sparse optimization to effectively decompose the data contributions into with and without anomalies for the purpose of anomaly detection and quantification. Further, the ideas of the directed graph are implemented on the estimated anomaly-free data to determine the root cause of anomaly to enable preventive maintenance. The efficacy of the proposed method is demonstrated on two case studies comprising of synthetic and real-time datasets.
To predict the output of a photovoltaic (PV) system, a variety of models are required, like plane-of-array (POA) irradiance transposition, cell/module temperature, and others depending on what meteorological data are ...
详细信息
ISBN:
(数字)9781665464260
ISBN:
(纸本)9781665475822
To predict the output of a photovoltaic (PV) system, a variety of models are required, like plane-of-array (POA) irradiance transposition, cell/module temperature, and others depending on what meteorological data are available. As the data flow through the modeling pipeline, uncertainties can arise. As these uncertainties accumulate, it can be difficult to determine whether the issues are due to measurement or modeling errors. When multiple models are being used in an estimation, there is no way to directly attribute errors to any one model specifically. Furthermore, when modeling pipelines are assessed independently, lacking a standardized process, it leads to irreproducible outcomes, making it challenging to conduct meaningful side-by-side comparison of different models. In an effort to decrease these uncertainties, a process for model validation was created for the commonly used models in the PV modeling pipeline. This process uses three different phases of analysis to gauge a model's performance: basic error analysis (RMSE, MBE, etc.), residual analysis, and baseline model comparison. This outline is demonstrated for irradiance transposition and decomposition, module temperature, incidence angle modifier (lAM), and PV performance modeling in the form of individual Jupyter Notebooks. Using a full year of hourly field data, these notebooks allow for modelers to evaluate their models at a wide range of conditions to determine seasonal or time-of-day performance. The annual energy yield is calculated using both modeled and measured values to observe the direct impact of the model's errors. The analysis also provides insight into which variables within the model could be negatively affecting the model's output. Using a well-established and validated model of the same type, the user's model is compared to the baseline model. Following this process will allow modelers and model developers to improve their tools and will ultimately result in lower uncertainty and more c
These This paper reviews two promising Urban Air Mobility electric VTOL designs and develops static performance models for them. Using America Commuter Survey LODES [1] data, a demand model for such a mobility service...
详细信息
ISBN:
(纸本)9781665405607
These This paper reviews two promising Urban Air Mobility electric VTOL designs and develops static performance models for them. Using America Commuter Survey LODES [1] data, a demand model for such a mobility service is also derived. Further, the performance model is then used to compare UAM service to driving to indicate demand and energy expenditure of this new emerging form of mobility.
暂无评论