Smart Wind Turbine Prediction Isikhombimsebenzisi Sokugcinwa Kokubikezela ngu-4Paradigm UED

Umdwebo Smart Wind Turbine Prediction Isikhombimsebenzisi Sokugcinwa Kokubikezela ngu-4Paradigm UED ungumnqobi ohlonishwa kakhulu womklomelo odumile we-2023 Umklomelo Wesiliva we-A' Design Award Esigabeni Somncintiswano se-Ukudizayina I-Inthafeyi.

IsilivaI-Inthafeyi· 2023

Smart Wind Turbine Prediction Isikhombimsebenzisi Sokugcinwa Kokubikezela

ngu 4Paradigm UED

Iklayenti: Jianxin Technology Co., Ltd

Umnqobi we-Umklomelo Wesiliva we-A' Design Award Esigabeni se-I-Inthafeyi

53,044

Umnqobi Womklomelo Oqinisekisiwe

Qinisekisa Isimo Somklomelo se-#141912

Vakashela Isayithi Buka ku-A' Design Award Isitatimende Sabezindaba Ibheji Yomklomelo

Imibala

Ukuklama

Mayelana ne-Smart Wind Turbine Prediction Isikhombimsebenzisi Sokugcinwa Kokubikezela

I-Smart Wind Turbine Prediction iyisikhombimsebenzisi sesofthiwe sokusebenza okuhlakaniphile nokugcinwa kwamapulazi omoya. Lesi sikhombimsebenzisi sisebenzisa ukuboniswa kwezinto ngokwezinhlangothi ezintathu, ukulingisa okungokoqobo namagrafu edatha ukukhombisa izimo zamathebhini nokuthola amaphutha ngokushesha. Amamodeli okufunda komshini ahlelwa ngokuhudula nokuwisa idatha nezilungiselelo zemodeli, ngakho izinhlobo zamathebhini eziyodwa noma eziningi zingafakwa. Izexwayiso zamaphutha zilethwa cishe emizuzwini engamashumi amabili ngaphambili ngokwesilinganiso, futhi ukunemba kwemodeli kufinyelela kumaphesenti angu-81. Izindleko zokugcinwa ngezandla nezingozi zokuphepha ziyancishiswa.

Ukuqashelwa

Mayelana ne-Umklomelo Wesiliva we-A' Design Award

Smart Wind Turbine Prediction Isikhombimsebenzisi Sokugcinwa Kokubikezela iwinile uMklomelo Wesiliva we-A' Design Award, ukwaziswa okuhloniphekile ngokungajwayelekile okunikezwa imiklamo esezingeni eliphezulu, ebukekayo nethinta kakhulu. Abawinile beSiliva yimisebenzi egqamile kakhulu nedala kakhulu ebonisa ubungcweti obuphawulekayo, italente nobuhlakani babaklami babo. Smart Wind Turbine Prediction Isikhombimsebenzisi Sokugcinwa Kokubikezela ilindeleke ukuba ibe ngumsebenzi omuhle wesibonelo, onobungcweti obuphawulekayo nezinto ezintsha ezijulile. Lo mklamo owinile uMklomelo Wesiliva we-A' Design Award uyinto entsha ebonakala kakhulu nethakazelisayo esiza futhi isunduza imingcele yobuciko, isayensi, ukuklama nobuchwepheshe. Smart Wind Turbine Prediction Isikhombimsebenzisi Sokugcinwa Kokubikezela iyinto enomhawu omkhulu kuyo evusa izifiso, ilethe imizwa emihle futhi ivuse ukumangala nokuxakeka.

Ngemuva Kokuklama

Iphakheji Yabezindaba

Ama-credit, amalungu eqembu nemininingwane yobuchwepheshe ehlinzekwe ngumklami.

Izici Ezihlukile: 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.
Izilinganiso Nokupakisha: Width 1920 Height 1080
Amathegi: AI System Design , AI , AI Applications , Machine Learning , Modeling , Big Data
Ubuchwepheshe Bokukhiqiza: 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%.
Inselele Yokudweba: It also enables more effective use of wind resources and contributes to the global governance effort to combat climate change.
Ucwaningo: It addresses user pain points of high manual operations and maintenance costs and improves operations and maintenance personnel safety and efficiency.
Ugqozi: 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.
Ubude Bephrojekthi: The project was completed in Beijing in 2022
Ukuhamba Kokusebenza: 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.
Amalungu Eqembu: Design Director：Yun Xu
Design Manager：Wei Wang
Designer：Shaoxiong Bai
Designer：Xinjie Li
Designer：Yanfen Zhang
Amakhredithi Ezithombe: Design creativity：Yun Xu , Wei Wang
Interface design: Yanfen Zhang
Interaction design：Xinjie Li
Video Copyright：Shaoxiong Bai