Smart Wind Turbine Prediction Interface para sa Predictive Maintenance by 4Paradigm UED is a highly esteemed winner of the very prestigious 2023 A' Design Award na Pilak in Disenyo ng Interface, Interaksyon at Karanasan ng Gumagamit Competition Category.
PilakInterface· 2023
Smart Wind Turbine Prediction Interface para sa Predictive Maintenance
Client: Jianxin Technology Co., Ltd
A' Design Award na Pilak Winner in Interface Category
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- Verified Award Winner
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The Design
About Smart Wind Turbine Prediction Interface para sa Predictive Maintenance
Ang Smart Wind Turbine Prediction ay isang software interface para sa matalinong operasyon at pagmementina ng mga wind farm. Gumagamit ang interface ng three-dimensional na visualization, virtual simulation at mga data graph upang ipakita ang kondisyon ng mga turbine at upang mabilis na matukoy ang lokasyon ng mga depekto. Ang mga machine learning model ay iko-configure sa pamamagitan ng pag-drag at pag-drop ng data at mga setting ng model, kaya maaaring saklawin ang isa o maramihang uri ng turbine. Ang mga babala sa depekto ay naihahatid nang humigit-kumulang dalawampung minuto nang mas maaga sa karaniwan, at ang katumpakan ng model ay umaabot sa 81 porsyento. Nababawasan ang mga gastos sa manu-manong pagmementina at mga panganib sa kaligtasan.
The Recognition
About the A' Design Award na Pilak
Ang Smart Wind Turbine Prediction Interface para sa Predictive Maintenance ay nagwagi ng A' Design Award na Pilak, isang pambihirang prestihiyosong pagkilalang iginagawad sa mga disenyong nasa pinakamataas na antas, nakabibighani at kahanga-hanga. Ang mga nagwagi ng Pilak ay mga likhang lubhang makinang at napakamalikhain na naglalarawan sa pambihirang kadalubhasaan, talento at talas ng isip ng kanilang mga tagapagdisenyo. Inaasahang ang Smart Wind Turbine Prediction Interface para sa Predictive Maintenance ay isang kahanga-hangang likhang huwaran na kapansin-pansing propesyonal at malalim na makabago. Ang disenyong ito na nagwagi ng A' Design Award na Pilak ay isang lubhang kapansin-pansin at hinahangaang imbensyon na nakikinabang at nagpapaunlad sa mga hangganan ng sining, agham, disenyo at teknolohiya. Ang Smart Wind Turbine Prediction Interface para sa Predictive Maintenance ay isang likhang labis na kinaiinggitan na gumigising ng mga hangarin, nagdadala ng positibong damdamin at nagpapasiklab ng pagkamangha at pagkabighani.
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
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