Smart Wind Turbine Prediction Interfaz de Mantenimiento Predictivo by 4Paradigm UED is a highly esteemed winner of the very prestigious 2023 A' Design Award de Plata in Diseño de Interfaz, Interacción y Experiencia de Usuario Competition Category.
PlataInterfaz· 2023
Smart Wind Turbine Prediction Interfaz de Mantenimiento Predictivo
Client: Jianxin Technology Co., Ltd
A' Design Award de Plata Winner in Interfaz Category
- 52,172
- Verified Award Winner
- Verify Award Status for #141912
The Design
About Smart Wind Turbine Prediction Interfaz de Mantenimiento Predictivo
Smart Wind Turbine Prediction es una interfaz de software para la operación y el mantenimiento inteligentes de parques eólicos. La interfaz emplea visualización tridimensional, simulación virtual y gráficos de datos para mostrar el estado de las turbinas y localizar fallos con rapidez. Los modelos de aprendizaje automático se configuran arrastrando y soltando los datos y los ajustes del modelo, de modo que pueden abarcarse uno o varios tipos de turbinas. Las alertas de fallo se emiten, en promedio, unos veinte minutos antes, y la precisión del modelo alcanza el 81 por ciento. Se reducen los costes de mantenimiento manual y los riesgos para la seguridad.
The Recognition
About the A' Design Award de Plata
Smart Wind Turbine Prediction Interfaz de Mantenimiento Predictivo ha ganado el A' Design Award de Plata, un reconocimiento extraordinariamente prestigioso concedido a diseños de gama alta, magníficos e impresionantes. Los ganadores de Plata son obras tremendamente brillantes y sumamente creativas que ilustran la destacada experiencia, el talento y la agudeza de sus diseñadores. Se espera que Smart Wind Turbine Prediction Interfaz de Mantenimiento Predictivo sea una obra maravillosa y emblemática, notablemente profesional y profundamente innovadora. Este diseño ganador del A' Design Award de Plata es una invención muy notable y admirada que beneficia y hace avanzar las fronteras del arte, la ciencia, el diseño y la tecnología. Smart Wind Turbine Prediction Interfaz de Mantenimiento Predictivo es una creación enormemente envidiada que evoca deseos, aporta sentimientos positivos y despierta asombro y admiración.
Behind the Design
Press Kit
Credits, team members and technical details provided by the designer.
- Unique Properties
- 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.
- Dimensions & Packaging
- Width 1920 Height 1080
- Tags
- AI System Design , AI , AI Applications , Machine Learning , Modeling , Big Data
- Production 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%.
- Design Challenge
- It also enables more effective use of wind resources and contributes to the global governance effort to combat climate change.
- Research
- It addresses user pain points of high manual operations and maintenance costs and improves operations and maintenance personnel safety and efficiency.
- 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.
- Project Duration
- The project was completed in Beijing in 2022
- Operation Flow
- 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.
- Team Members
- Design Director：Yun Xu
Design Manager：Wei Wang
Designer：Shaoxiong Bai
Designer：Xinjie Li
Designer：Yanfen Zhang - Image Credits
- Design creativity：Yun Xu , Wei Wang
Interface design: Yanfen Zhang
Interaction design：Xinjie Li
Video Copyright：Shaoxiong Bai
Sponsored
Explore Beyond Designers.org
Discover products, services and opportunities from our advertising partners.
More to Explore
Related Designs
Explore more award-winning designs from the same category, selected by merit.
