Dizayn Smart Wind Turbine Prediction Entèfas Antretyen Prediktif pa 4Paradigm UED se yon gayan ki gen anpil estim nan konpetisyon trè prestijye 2023 A' Design Award Ajan nan Kategori Konpetisyon Entèfas.
AjanEntèfas· 2023
Smart Wind Turbine Prediction Entèfas Antretyen Prediktif
Kliyan: Jianxin Technology Co., Ltd
Gayan A' Design Award Ajan nan Kategori Entèfas
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Verifye Estati Pri pou #141912Konsepsyon an
Konsènan Smart Wind Turbine Prediction Entèfas Antretyen Prediktif
Smart Wind Turbine Prediction se yon entèfas lojisyèl pou operasyon ak antretyen entèlijan pak eolyèn yo. Entèfas la itilize vizyalizasyon twa dimansyon, simulation vityèl ak grafik done pou montre kondisyon tibin yo epi pou lokalize pann yo byen vit. Modèl aprantisaj otomatik yo konfigire lè ou trennen epi depoze done ak paramèt modèl yo, kidonk yon sèl tip tibin oswa plizyè tip tibin ka kouvri. Avètisman sou pann yo rive apeprè ven minit pi bonè an mwayèn, epi presizyon modèl la rive nan 81 pousan. Kou antretyen manyèl yo ak risk sekirite yo diminye.
Rekonesans lan
Konsènan A' Design Award Ajan
Smart Wind Turbine Prediction Entèfas Antretyen Prediktif se yon ganyan A' Design Award Ajan, yon rekonesans ki gen yon prestij enmans yo bay design nivo siperyè, bèl anpil e enpresyonan. Ganyan Ajan yo se travay ki trè briyan e ki trè kreyatif ki montre ekspètiz, talan ak finès designer yo. Yo atann Smart Wind Turbine Prediction Entèfas Antretyen Prediktif pou se yon bèl travay modèl, remakab nan pwofesyonalis e ki gen gwo inovasyon. Design sa a ki ganyen A' Design Award Ajan se yon envansyon trè remakab, admire ki pote benefis e ki pouse limit atizay, syans, design ak teknoloji. Smart Wind Turbine Prediction Entèfas Antretyen Prediktif se yon kreyasyon anpil moun jalou ki reveye dezi, ki pote santiman pozitif e ki limen sipriz ak mèvèy.
Dèyè Konsepsyon an
Dosye Laprès
Kredi, manm ekip ak detay teknik konseptè a bay.
- Pwopriyete Inik
- 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.
- Dimansyon & Anbalaj
- Width 1920 Height 1080
- Etikèt
- AI System Design , AI , AI Applications , Machine Learning , Modeling , Big Data
- Teknoloji Pwodiksyon
- 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%.
- Defi Dizayn
- It also enables more effective use of wind resources and contributes to the global governance effort to combat climate change.
- Rechèch
- It addresses user pain points of high manual operations and maintenance costs and improves operations and maintenance personnel safety and efficiency.
- Enspirasyon
- 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.
- Dire Pwojè
- The project was completed in Beijing in 2022
- Fliks Operasyon
- 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.
- Manm Ekip
- Design Director:Yun Xu
Design Manager:Wei Wang
Designer:Shaoxiong Bai
Designer:Xinjie Li
Designer:Yanfen Zhang - Kredi Imaj
- Design creativity:Yun Xu , Wei Wang
Interface design: Yanfen Zhang
Interaction design:Xinjie Li
Video Copyright:Shaoxiong Bai
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