Multi-model fusion method for predicting service life of wind turbine generator
The invention provides a multi-model fusion method for predicting the service life of a wind turbine generator, which can comprehensively use various data and models to improve the stability and reliability of service life prediction. The method comprises the following steps of S101, data collection...
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| creator | XU BUFENG XU JIN FAN XUANFANG ZHENG JIANFEI BAI JIAN ZHANG XIAOHUI DENG WEI WANG ZHEN ZHANG CHANG'AN LI JIASHAN |
| description | The invention provides a multi-model fusion method for predicting the service life of a wind turbine generator, which can comprehensively use various data and models to improve the stability and reliability of service life prediction. The method comprises the following steps of S101, data collection and preprocessing, S102, model construction and model training, S103, model fusion and model evaluation, and S104, model application and model updating.
本发明提供了风电机组寿命预测的多模型融合方法，其能够综合运用多种数据和模型，提高寿命预测的稳定性和可靠性。其包括如下步骤：S101、数据收集和预处理S102、模型构建和模型训练S103、模型融合和模型评估S104、模型应用和模型更新。 |
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本发明提供了风电机组寿命预测的多模型融合方法，其能够综合运用多种数据和模型，提高寿命预测的稳定性和可靠性。其包括如下步骤：S101、数据收集和预处理S102、模型构建和模型训练S103、模型融合和模型评估S104、模型应用和模型更新。</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS</subject><creationdate>2023</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20231117&DB=EPODOC&CC=CN&NR=117077532A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76289</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20231117&DB=EPODOC&CC=CN&NR=117077532A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>XU BUFENG</creatorcontrib><creatorcontrib>XU JIN</creatorcontrib><creatorcontrib>FAN XUANFANG</creatorcontrib><creatorcontrib>ZHENG JIANFEI</creatorcontrib><creatorcontrib>BAI JIAN</creatorcontrib><creatorcontrib>ZHANG XIAOHUI</creatorcontrib><creatorcontrib>DENG WEI</creatorcontrib><creatorcontrib>WANG ZHEN</creatorcontrib><creatorcontrib>ZHANG CHANG'AN</creatorcontrib><creatorcontrib>LI JIASHAN</creatorcontrib><title>Multi-model fusion method for predicting service life of wind turbine generator</title><description>The invention provides a multi-model fusion method for predicting the service life of a wind turbine generator, which can comprehensively use various data and models to improve the stability and reliability of service life prediction. The method comprises the following steps of S101, data collection and preprocessing, S102, model construction and model training, S103, model fusion and model evaluation, and S104, model application and model updating.
本发明提供了风电机组寿命预测的多模型融合方法，其能够综合运用多种数据和模型，提高寿命预测的稳定性和可靠性。其包括如下步骤：S101、数据收集和预处理S102、模型构建和模型训练S103、模型融合和模型评估S104、模型应用和模型更新。</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNyrEKwjAQANAsDqL-w_kBBWuRzFIUF3VxLzG5tAdpLlwS_X0d_ACnt7ylul9rKNTM7DCAr5k4woxlYgeeBZKgI1sojpBRXmQRAnkE9vCm6KBUeVJEGDGimMKyVgtvQsbNz5Xank-P_tJg4gFzMvY7y9Df2lbvtD50-2P3z_kAbTI3Hg</recordid><startdate>20231117</startdate><enddate>20231117</enddate><creator>XU BUFENG</creator><creator>XU JIN</creator><creator>FAN XUANFANG</creator><creator>ZHENG JIANFEI</creator><creator>BAI JIAN</creator><creator>ZHANG XIAOHUI</creator><creator>DENG WEI</creator><creator>WANG ZHEN</creator><creator>ZHANG CHANG'AN</creator><creator>LI JIASHAN</creator><scope>EVB</scope></search><sort><creationdate>20231117</creationdate><title>Multi-model fusion method for predicting service life of wind turbine generator</title><author>XU BUFENG ; XU JIN ; FAN XUANFANG ; ZHENG JIANFEI ; BAI JIAN ; ZHANG XIAOHUI ; DENG WEI ; WANG ZHEN ; ZHANG CHANG'AN ; LI JIASHAN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN117077532A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2023</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>XU BUFENG</creatorcontrib><creatorcontrib>XU JIN</creatorcontrib><creatorcontrib>FAN XUANFANG</creatorcontrib><creatorcontrib>ZHENG JIANFEI</creatorcontrib><creatorcontrib>BAI JIAN</creatorcontrib><creatorcontrib>ZHANG XIAOHUI</creatorcontrib><creatorcontrib>DENG WEI</creatorcontrib><creatorcontrib>WANG ZHEN</creatorcontrib><creatorcontrib>ZHANG CHANG'AN</creatorcontrib><creatorcontrib>LI JIASHAN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>XU BUFENG</au><au>XU JIN</au><au>FAN XUANFANG</au><au>ZHENG JIANFEI</au><au>BAI JIAN</au><au>ZHANG XIAOHUI</au><au>DENG WEI</au><au>WANG ZHEN</au><au>ZHANG CHANG'AN</au><au>LI JIASHAN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Multi-model fusion method for predicting service life of wind turbine generator</title><date>2023-11-17</date><risdate>2023</risdate><abstract>The invention provides a multi-model fusion method for predicting the service life of a wind turbine generator, which can comprehensively use various data and models to improve the stability and reliability of service life prediction. The method comprises the following steps of S101, data collection and preprocessing, S102, model construction and model training, S103, model fusion and model evaluation, and S104, model application and model updating.
本发明提供了风电机组寿命预测的多模型融合方法，其能够综合运用多种数据和模型，提高寿命预测的稳定性和可靠性。其包括如下步骤：S101、数据收集和预处理S102、模型构建和模型训练S103、模型融合和模型评估S104、模型应用和模型更新。</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
| title | Multi-model fusion method for predicting service life of wind turbine generator |
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