Treatment device and detection method for aging degree and substitution rate of steel slag sand
The invention discloses a treatment device and a detection method for the aging degree and the substitution rate of steel slag sand, and the detection method for the aging degree of the steel slag sand comprises the following steps: aging the steel slag sand; acquiring image data of the aged steel s...
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| creator | CHEN HOUGENG DENG ZHONGHUA HU DI TENG SHENGJIE ZHU LIN JIN QIANG WU CHANGGENG LI YUNZE |
| description | The invention discloses a treatment device and a detection method for the aging degree and the substitution rate of steel slag sand, and the detection method for the aging degree of the steel slag sand comprises the following steps: aging the steel slag sand; acquiring image data of the aged steel slag sand to form a steel slag sand image data set; constructing an SE-ConvNeXt network model according to the steel slag sand image data set; using the constructed SE-ConvNeXt network model to carry out iterative training on the training data set in the step S1 to the step S3, so as to obtain a deep learning model; and the SE-ConvNeXt network model is used for identifying the aging degree of the steel slag sand of the data set which is not marked.
本发明公开了一种钢渣砂陈化程度及取代率的处理装置以及检测方法，其中一种钢渣砂陈化程度的检测方法，包括以下步骤：对钢渣砂进行陈化处理；获取陈化处理后的钢渣砂的图像数据以形成钢渣砂图像数据集；根据所述钢渣砂图像数据集构建SE-ConvNeXt网络模型；利用构建的SE-ConvNeXt网络模型对上述S1-S3的训练数据集进行迭代训练，以获得到深度学习模型；利用SE-ConvNeXt网络模型对未经过标注过数据集进行识别其钢渣砂的陈化程度。 |
| format | Patent |
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本发明公开了一种钢渣砂陈化程度及取代率的处理装置以及检测方法，其中一种钢渣砂陈化程度的检测方法，包括以下步骤：对钢渣砂进行陈化处理；获取陈化处理后的钢渣砂的图像数据以形成钢渣砂图像数据集；根据所述钢渣砂图像数据集构建SE-ConvNeXt网络模型；利用构建的SE-ConvNeXt网络模型对上述S1-S3的训练数据集进行迭代训练，以获得到深度学习模型；利用SE-ConvNeXt网络模型对未经过标注过数据集进行识别其钢渣砂的陈化程度。</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ; PHYSICS</subject><creationdate>2024</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=20240416&DB=EPODOC&CC=CN&NR=117893487A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240416&DB=EPODOC&CC=CN&NR=117893487A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>CHEN HOUGENG</creatorcontrib><creatorcontrib>DENG ZHONGHUA</creatorcontrib><creatorcontrib>HU DI</creatorcontrib><creatorcontrib>TENG SHENGJIE</creatorcontrib><creatorcontrib>ZHU LIN</creatorcontrib><creatorcontrib>JIN QIANG</creatorcontrib><creatorcontrib>WU CHANGGENG</creatorcontrib><creatorcontrib>LI YUNZE</creatorcontrib><title>Treatment device and detection method for aging degree and substitution rate of steel slag sand</title><description>The invention discloses a treatment device and a detection method for the aging degree and the substitution rate of steel slag sand, and the detection method for the aging degree of the steel slag sand comprises the following steps: aging the steel slag sand; acquiring image data of the aged steel slag sand to form a steel slag sand image data set; constructing an SE-ConvNeXt network model according to the steel slag sand image data set; using the constructed SE-ConvNeXt network model to carry out iterative training on the training data set in the step S1 to the step S3, so as to obtain a deep learning model; and the SE-ConvNeXt network model is used for identifying the aging degree of the steel slag sand of the data set which is not marked.
本发明公开了一种钢渣砂陈化程度及取代率的处理装置以及检测方法，其中一种钢渣砂陈化程度的检测方法，包括以下步骤：对钢渣砂进行陈化处理；获取陈化处理后的钢渣砂的图像数据以形成钢渣砂图像数据集；根据所述钢渣砂图像数据集构建SE-ConvNeXt网络模型；利用构建的SE-ConvNeXt网络模型对上述S1-S3的训练数据集进行迭代训练，以获得到深度学习模型；利用SE-ConvNeXt网络模型对未经过标注过数据集进行识别其钢渣砂的陈化程度。</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNyjEKwkAQheFtLES9w3gAixAhsZSgWFmlD2Pydl3Y7Iadiec3qAewej-8b226NoN1RFQa8PI9iOOwpKJXnyKN0GcayKZM7Hx0y-Uyvkrmh6jX-QMzKyhZEgUCSWBHsqCtWVkOgt1vN2Z_vbTN7YApdZCJe0Ro19yLoqpP5bGuzuU_5g1qWTzR</recordid><startdate>20240416</startdate><enddate>20240416</enddate><creator>CHEN HOUGENG</creator><creator>DENG ZHONGHUA</creator><creator>HU DI</creator><creator>TENG SHENGJIE</creator><creator>ZHU LIN</creator><creator>JIN QIANG</creator><creator>WU CHANGGENG</creator><creator>LI YUNZE</creator><scope>EVB</scope></search><sort><creationdate>20240416</creationdate><title>Treatment device and detection method for aging degree and substitution rate of steel slag sand</title><author>CHEN HOUGENG ; DENG ZHONGHUA ; HU DI ; TENG SHENGJIE ; ZHU LIN ; JIN QIANG ; WU CHANGGENG ; LI YUNZE</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN117893487A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>CHEN HOUGENG</creatorcontrib><creatorcontrib>DENG ZHONGHUA</creatorcontrib><creatorcontrib>HU DI</creatorcontrib><creatorcontrib>TENG SHENGJIE</creatorcontrib><creatorcontrib>ZHU LIN</creatorcontrib><creatorcontrib>JIN QIANG</creatorcontrib><creatorcontrib>WU CHANGGENG</creatorcontrib><creatorcontrib>LI YUNZE</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>CHEN HOUGENG</au><au>DENG ZHONGHUA</au><au>HU DI</au><au>TENG SHENGJIE</au><au>ZHU LIN</au><au>JIN QIANG</au><au>WU CHANGGENG</au><au>LI YUNZE</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Treatment device and detection method for aging degree and substitution rate of steel slag sand</title><date>2024-04-16</date><risdate>2024</risdate><abstract>The invention discloses a treatment device and a detection method for the aging degree and the substitution rate of steel slag sand, and the detection method for the aging degree of the steel slag sand comprises the following steps: aging the steel slag sand; acquiring image data of the aged steel slag sand to form a steel slag sand image data set; constructing an SE-ConvNeXt network model according to the steel slag sand image data set; using the constructed SE-ConvNeXt network model to carry out iterative training on the training data set in the step S1 to the step S3, so as to obtain a deep learning model; and the SE-ConvNeXt network model is used for identifying the aging degree of the steel slag sand of the data set which is not marked.
本发明公开了一种钢渣砂陈化程度及取代率的处理装置以及检测方法，其中一种钢渣砂陈化程度的检测方法，包括以下步骤：对钢渣砂进行陈化处理；获取陈化处理后的钢渣砂的图像数据以形成钢渣砂图像数据集；根据所述钢渣砂图像数据集构建SE-ConvNeXt网络模型；利用构建的SE-ConvNeXt网络模型对上述S1-S3的训练数据集进行迭代训练，以获得到深度学习模型；利用SE-ConvNeXt网络模型对未经过标注过数据集进行识别其钢渣砂的陈化程度。</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS |
| title | Treatment device and detection method for aging degree and substitution rate of steel slag sand |
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