Gear surface defect detection method based on RDMS
A gear surface defect detection method based on RDMS comprises the following steps: Step 1, acquiring gear surface images including a normal tooth surface image and a defective tooth surface image; step 2, establishing a tooth surface image data set; 3, an RDMS network model is constructed; step 4,...
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| creator | LYU CHENGZHI LI SHAOKANG ZHANG LEI CHEN ZIHENG BI DONG |
| description | A gear surface defect detection method based on RDMS comprises the following steps: Step 1, acquiring gear surface images including a normal tooth surface image and a defective tooth surface image; step 2, establishing a tooth surface image data set; 3, an RDMS network model is constructed; step 4, training the RDMS network model based on the tooth surface image data set; and Step 5, performing defect detection on the surface image of the gear to be detected. According to the method, only the normal gear surface image is used in the training process, the difficulty of manual collection and defect sample marking is eliminated, meanwhile, the detection precision in the detection process is high, pixel-level defect positioning can be provided, the training threshold is lowered, the use efficiency is improved, and the method has extremely high generalization.
一种基于RDMS的齿轮表面缺陷检测方法，步骤为：Step1、采集齿轮表面图像，包括正常齿面图像和有缺陷的齿面图像；Step2、建立齿面图像数据集；Step3、构建RDMS网络模型；Step4、基于齿面图像数据集对RDMS网络模型进行训练；Step5、对待检测的齿轮表面图像进行缺陷检测。本发明能够通过在训练过程中 |
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一种基于RDMS的齿轮表面缺陷检测方法，步骤为：Step1、采集齿轮表面图像，包括正常齿面图像和有缺陷的齿面图像；Step2、建立齿面图像数据集；Step3、构建RDMS网络模型；Step4、基于齿面图像数据集对RDMS网络模型进行训练；Step5、对待检测的齿轮表面图像进行缺陷检测。本发明能够通过在训练过程中</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>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=20231205&DB=EPODOC&CC=CN&NR=117173098A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25543,76293</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20231205&DB=EPODOC&CC=CN&NR=117173098A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>LYU CHENGZHI</creatorcontrib><creatorcontrib>LI SHAOKANG</creatorcontrib><creatorcontrib>ZHANG LEI</creatorcontrib><creatorcontrib>CHEN ZIHENG</creatorcontrib><creatorcontrib>BI DONG</creatorcontrib><title>Gear surface defect detection method based on RDMS</title><description>A gear surface defect detection method based on RDMS comprises the following steps: Step 1, acquiring gear surface images including a normal tooth surface image and a defective tooth surface image; step 2, establishing a tooth surface image data set; 3, an RDMS network model is constructed; step 4, training the RDMS network model based on the tooth surface image data set; and Step 5, performing defect detection on the surface image of the gear to be detected. According to the method, only the normal gear surface image is used in the training process, the difficulty of manual collection and defect sample marking is eliminated, meanwhile, the detection precision in the detection process is high, pixel-level defect positioning can be provided, the training threshold is lowered, the use efficiency is improved, and the method has extremely high generalization.
一种基于RDMS的齿轮表面缺陷检测方法，步骤为：Step1、采集齿轮表面图像，包括正常齿面图像和有缺陷的齿面图像；Step2、建立齿面图像数据集；Step3、构建RDMS网络模型；Step4、基于齿面图像数据集对RDMS网络模型进行训练；Step5、对待检测的齿轮表面图像进行缺陷检测。本发明能够通过在训练过程中</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>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZDByT00sUiguLUpLTE5VSElNS00uAVIlQCozP08hN7UkIz9FISmxODVFAcgPcvEN5mFgTUvMKU7lhdLcDIpuriHOHrqpBfnxqcUFQIPyUkvinf0MDc0NzY0NLC0cjYlRAwBs1iso</recordid><startdate>20231205</startdate><enddate>20231205</enddate><creator>LYU CHENGZHI</creator><creator>LI SHAOKANG</creator><creator>ZHANG LEI</creator><creator>CHEN ZIHENG</creator><creator>BI DONG</creator><scope>EVB</scope></search><sort><creationdate>20231205</creationdate><title>Gear surface defect detection method based on RDMS</title><author>LYU CHENGZHI ; LI SHAOKANG ; ZHANG LEI ; CHEN ZIHENG ; BI DONG</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN117173098A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2023</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>LYU CHENGZHI</creatorcontrib><creatorcontrib>LI SHAOKANG</creatorcontrib><creatorcontrib>ZHANG LEI</creatorcontrib><creatorcontrib>CHEN ZIHENG</creatorcontrib><creatorcontrib>BI DONG</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>LYU CHENGZHI</au><au>LI SHAOKANG</au><au>ZHANG LEI</au><au>CHEN ZIHENG</au><au>BI DONG</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Gear surface defect detection method based on RDMS</title><date>2023-12-05</date><risdate>2023</risdate><abstract>A gear surface defect detection method based on RDMS comprises the following steps: Step 1, acquiring gear surface images including a normal tooth surface image and a defective tooth surface image; step 2, establishing a tooth surface image data set; 3, an RDMS network model is constructed; step 4, training the RDMS network model based on the tooth surface image data set; and Step 5, performing defect detection on the surface image of the gear to be detected. According to the method, only the normal gear surface image is used in the training process, the difficulty of manual collection and defect sample marking is eliminated, meanwhile, the detection precision in the detection process is high, pixel-level defect positioning can be provided, the training threshold is lowered, the use efficiency is improved, and the method has extremely high generalization.
一种基于RDMS的齿轮表面缺陷检测方法，步骤为：Step1、采集齿轮表面图像，包括正常齿面图像和有缺陷的齿面图像；Step2、建立齿面图像数据集；Step3、构建RDMS网络模型；Step4、基于齿面图像数据集对RDMS网络模型进行训练；Step5、对待检测的齿轮表面图像进行缺陷检测。本发明能够通过在训练过程中</abstract><oa>free_for_read</oa></addata></record> |
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| title | Gear surface defect detection method based on RDMS |
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