Study on the quality detection method of biochar based on red–green–blue image recognition technology
In order to quickly adjust the production process of biochar, keep the consistency of production conditions and reduce the production cost of biochar. In this paper, maize straw and rice husk were used as raw material for biochar preparation under 350–600 o C fully pyrolyzed by fixed bed quartz tube...
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| Veröffentlicht in: | Biomass conversion and biorefinery 2023-08, Vol.13 (13), p.11533-11541 |
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| container_issue | 13 |
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| container_title | Biomass conversion and biorefinery |
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| creator | Mingfeng, Wang Aihua, Xiang Luhan, Yang Xuan, Zhong Zhengyan, Zhang Zhennan, Gao Encheng, Jiang |
| description | In order to quickly adjust the production process of biochar, keep the consistency of production conditions and reduce the production cost of biochar. In this paper, maize straw and rice husk were used as raw material for biochar preparation under 350–600
o
C fully pyrolyzed by fixed bed quartz tube pyrolysis device. The image recognition technology was used to acquire the RGB value of biochar and translated into gray value. The relationship between gray value and pyrolysis temperature, proximate analysis, and calorific value was studied; the result showed that the gray value had a strong linear relationship with carbonization temperature. Moreover, the relationships between gray scale and volatile, fixed carbon met the
DoseResp
mold; the
R
2
reached nearly 0.999. However, the correlations between gray value and ash and net calorific value were weak. This study provided theoretical support for the rapid detection of biochar and timely feedback of large-scale production conditions of biochar. |
| doi_str_mv | 10.1007/s13399-021-01957-1 |
| format | Article |
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o
C fully pyrolyzed by fixed bed quartz tube pyrolysis device. The image recognition technology was used to acquire the RGB value of biochar and translated into gray value. The relationship between gray value and pyrolysis temperature, proximate analysis, and calorific value was studied; the result showed that the gray value had a strong linear relationship with carbonization temperature. Moreover, the relationships between gray scale and volatile, fixed carbon met the
DoseResp
mold; the
R
2
reached nearly 0.999. However, the correlations between gray value and ash and net calorific value were weak. This study provided theoretical support for the rapid detection of biochar and timely feedback of large-scale production conditions of biochar.</description><identifier>ISSN: 2190-6815</identifier><identifier>EISSN: 2190-6823</identifier><identifier>DOI: 10.1007/s13399-021-01957-1</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Biotechnology ; Calorific value ; Energy ; Fixed beds ; Image acquisition ; Original Article ; Production costs ; Pyrolysis ; Raw materials ; Renewable and Green Energy</subject><ispartof>Biomass conversion and biorefinery, 2023-08, Vol.13 (13), p.11533-11541</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021</rights><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021.</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c270t-313f983813606df81f8b2944e1637e07da86586d98411cf40ba83a35fd58f4103</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s13399-021-01957-1$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s13399-021-01957-1$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Mingfeng, Wang</creatorcontrib><creatorcontrib>Aihua, Xiang</creatorcontrib><creatorcontrib>Luhan, Yang</creatorcontrib><creatorcontrib>Xuan, Zhong</creatorcontrib><creatorcontrib>Zhengyan, Zhang</creatorcontrib><creatorcontrib>Zhennan, Gao</creatorcontrib><creatorcontrib>Encheng, Jiang</creatorcontrib><title>Study on the quality detection method of biochar based on red–green–blue image recognition technology</title><title>Biomass conversion and biorefinery</title><addtitle>Biomass Conv. Bioref</addtitle><description>In order to quickly adjust the production process of biochar, keep the consistency of production conditions and reduce the production cost of biochar. In this paper, maize straw and rice husk were used as raw material for biochar preparation under 350–600
o
C fully pyrolyzed by fixed bed quartz tube pyrolysis device. The image recognition technology was used to acquire the RGB value of biochar and translated into gray value. The relationship between gray value and pyrolysis temperature, proximate analysis, and calorific value was studied; the result showed that the gray value had a strong linear relationship with carbonization temperature. Moreover, the relationships between gray scale and volatile, fixed carbon met the
DoseResp
mold; the
R
2
reached nearly 0.999. However, the correlations between gray value and ash and net calorific value were weak. This study provided theoretical support for the rapid detection of biochar and timely feedback of large-scale production conditions of biochar.</description><subject>Biotechnology</subject><subject>Calorific value</subject><subject>Energy</subject><subject>Fixed beds</subject><subject>Image acquisition</subject><subject>Original Article</subject><subject>Production costs</subject><subject>Pyrolysis</subject><subject>Raw materials</subject><subject>Renewable and Green Energy</subject><issn>2190-6815</issn><issn>2190-6823</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kE1OwzAQhSMEEhX0AqwisQ7MePLjLFHFn1SJBbC2kthOUqVxayeL7LgDN-QkuA2CHasZzbzvzegFwRXCDQJktw6J8jwChhFgnmQRngQLhjlEKWd0-ttjch4sndsAAKOMOMEiaF-HUU6h6cOhUeF-LLp2mEKpBlUNrZ9u1dAYGRodlq2pmsKGZeGUPABWya-Pz9oq1ftadqMK221RK7-oTN23R977NL3pTD1dBme66Jxa_tSL4P3h_m31FK1fHp9Xd-uoYhkMESHpnBNHSiGVmqPmJcvjWGFKmYJMFjxNeCpzHiNWOoay4FRQomXCdYxAF8H17LuzZj8qN4iNGW3vTwrGE4KEUU5exWZVZY1zVmmxs_57OwkEcUhVzKkKn6o4pirQQzRDzov7Wtk_63-ob15lfAg</recordid><startdate>20230801</startdate><enddate>20230801</enddate><creator>Mingfeng, Wang</creator><creator>Aihua, Xiang</creator><creator>Luhan, Yang</creator><creator>Xuan, Zhong</creator><creator>Zhengyan, Zhang</creator><creator>Zhennan, Gao</creator><creator>Encheng, Jiang</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20230801</creationdate><title>Study on the quality detection method of biochar based on red–green–blue image recognition technology</title><author>Mingfeng, Wang ; Aihua, Xiang ; Luhan, Yang ; Xuan, Zhong ; Zhengyan, Zhang ; Zhennan, Gao ; Encheng, Jiang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c270t-313f983813606df81f8b2944e1637e07da86586d98411cf40ba83a35fd58f4103</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Biotechnology</topic><topic>Calorific value</topic><topic>Energy</topic><topic>Fixed beds</topic><topic>Image acquisition</topic><topic>Original Article</topic><topic>Production costs</topic><topic>Pyrolysis</topic><topic>Raw materials</topic><topic>Renewable and Green Energy</topic><toplevel>online_resources</toplevel><creatorcontrib>Mingfeng, Wang</creatorcontrib><creatorcontrib>Aihua, Xiang</creatorcontrib><creatorcontrib>Luhan, Yang</creatorcontrib><creatorcontrib>Xuan, Zhong</creatorcontrib><creatorcontrib>Zhengyan, Zhang</creatorcontrib><creatorcontrib>Zhennan, Gao</creatorcontrib><creatorcontrib>Encheng, Jiang</creatorcontrib><collection>CrossRef</collection><jtitle>Biomass conversion and biorefinery</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mingfeng, Wang</au><au>Aihua, Xiang</au><au>Luhan, Yang</au><au>Xuan, Zhong</au><au>Zhengyan, Zhang</au><au>Zhennan, Gao</au><au>Encheng, Jiang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Study on the quality detection method of biochar based on red–green–blue image recognition technology</atitle><jtitle>Biomass conversion and biorefinery</jtitle><stitle>Biomass Conv. Bioref</stitle><date>2023-08-01</date><risdate>2023</risdate><volume>13</volume><issue>13</issue><spage>11533</spage><epage>11541</epage><pages>11533-11541</pages><issn>2190-6815</issn><eissn>2190-6823</eissn><abstract>In order to quickly adjust the production process of biochar, keep the consistency of production conditions and reduce the production cost of biochar. In this paper, maize straw and rice husk were used as raw material for biochar preparation under 350–600
o
C fully pyrolyzed by fixed bed quartz tube pyrolysis device. The image recognition technology was used to acquire the RGB value of biochar and translated into gray value. The relationship between gray value and pyrolysis temperature, proximate analysis, and calorific value was studied; the result showed that the gray value had a strong linear relationship with carbonization temperature. Moreover, the relationships between gray scale and volatile, fixed carbon met the
DoseResp
mold; the
R
2
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| language | eng |
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| source | SpringerNature Journals |
| subjects | Biotechnology Calorific value Energy Fixed beds Image acquisition Original Article Production costs Pyrolysis Raw materials Renewable and Green Energy |
| title | Study on the quality detection method of biochar based on red–green–blue image recognition technology |
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