DESIGN NAME: Smart Wind Turbine Prediction
PRIMARY FUNCTION: AI System Design
INSPIRATION: The system is an intelligent operation solution for renewable energy scenarios based on the digital base of Industrial IoT and the prediction capability of machine learning models. It provides decision support for the wind farm's intelligent operation and maintenance, turbine start/stop, and fault analysis.The system provides manageability for power generation capacity and allows stable and continuous output through intelligent, decision-driven solutions.
UNIQUE PROPERTIES / PROJECT DESCRIPTION: Through the visualization of wind turbine models and data graphs, we can quickly pinpoint the fault in wind turbines and efficiently safeguard the operations and maintenance process. Through the “drag and drop” data and model settings, we can meet the custom settings of “same type and same module” and “multiple types and multiple modules” from various machine learning models to hone targeted operations and maintenance trouble-shooting capabilities.
OPERATION / FLOW / INTERACTION: The design language follows the principle of intelligence and efficiency, and it aims to deliver a brand-new experience to users through digital and intelligent interactions.
PROJECT DURATION AND LOCATION: The project was completed in Beijing in 2022
FITS BEST INTO CATEGORY: Interface, Interaction and User Experience Design
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PRODUCTION / REALIZATION TECHNOLOGY: Using 3D visualization modeling, virtual simulation, surveillance visualization, and other technical means, we intelligently display the physical reality space in the digital system, provide interpretable and traceable machine learning capabilities, and simulate the logic behind users’ real interactive operations in the physical world. Our solution enables enterprise customers to receive fault warnings (on average) 20 minutes earlier, and the overall model accuracy rate has reached 81%.
SPECIFICATIONS / TECHNICAL PROPERTIES: Width 1920 Height 1080
TAGS: AI System Design , AI , AI Applications , Machine Learning , Modeling , Big Data
RESEARCH ABSTRACT: It addresses user pain points of high manual operations and maintenance costs and improves operations and maintenance personnel safety and efficiency.
CHALLENGE: It also enables more effective use of wind resources and contributes to the global governance effort to combat climate change.
ADDED DATE: 2022-06-13 09:04:54
TEAM MEMBERS (5) : Design Director:Yun Xu, Design Manager:Wei Wang, Designer:Shaoxiong Bai, Designer:Xinjie Li and Designer:Yanfen Zhang
IMAGE CREDITS: Design creativity:Yun Xu , Wei Wang
Interface design: Yanfen Zhang
Interaction design:Xinjie Li
Video Copyright:Shaoxiong Bai
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