Quantitative characterization of physical structure on carbon fiber surface based on image technique
In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circu...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ruan, Ruyu [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2020transfer abstract |
|---|
| Schlagwörter: |
|---|
| Übergeordnetes Werk: |
Enthalten in: Industrial Tourism: Opportunities for City and Enterprise - 2011, s.l. |
|---|---|
| Übergeordnetes Werk: |
volume:185 ; year:2020 ; day:5 ; month:01 ; pages:0 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.matdes.2019.108225 |
|---|
| Katalog-ID: |
ELV048939196 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | ELV048939196 | ||
| 003 | DE-627 | ||
| 005 | 20230626023116.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 200108s2020 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.matdes.2019.108225 |2 doi | |
| 028 | 5 | 2 | |a /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000857.pica |
| 035 | |a (DE-627)ELV048939196 | ||
| 035 | |a (ELSEVIER)S0264-1275(19)30663-X | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 380 |q VZ |
| 082 | 0 | 4 | |a 610 |q VZ |
| 082 | 0 | 4 | |a 530 |a 510 |a 000 |q VZ |
| 084 | |a 33.06 |2 bkl | ||
| 100 | 1 | |a Ruan, Ruyu |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Quantitative characterization of physical structure on carbon fiber surface based on image technique |
| 264 | 1 | |c 2020transfer abstract | |
| 336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
| 337 | |a nicht spezifiziert |b z |2 rdamedia | ||
| 338 | |a nicht spezifiziert |b zu |2 rdacarrier | ||
| 520 | |a In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness. | ||
| 520 | |a In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness. | ||
| 650 | 7 | |a Groove size |2 Elsevier | |
| 650 | 7 | |a Surface physical structure |2 Elsevier | |
| 650 | 7 | |a Quantitative characterization |2 Elsevier | |
| 650 | 7 | |a Groove shape |2 Elsevier | |
| 650 | 7 | |a Surface roughness |2 Elsevier | |
| 650 | 7 | |a Carbon fiber |2 Elsevier | |
| 700 | 1 | |a Cao, Weiyu |4 oth | |
| 700 | 1 | |a Xu, Lianghua |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier |t Industrial Tourism: Opportunities for City and Enterprise |d 2011 |g s.l. |w (DE-627)ELV036319309 |
| 773 | 1 | 8 | |g volume:185 |g year:2020 |g day:5 |g month:01 |g pages:0 |
| 856 | 4 | 0 | |u https://doi.org/10.1016/j.matdes.2019.108225 |3 Volltext |
| 912 | |a GBV_USEFLAG_U | ||
| 912 | |a GBV_ELV | ||
| 912 | |a SYSFLAG_U | ||
| 912 | |a SSG-OPC-MAT | ||
| 936 | b | k | |a 33.06 |j Mathematische Methoden der Physik |q VZ |
| 951 | |a AR | ||
| 952 | |d 185 |j 2020 |b 5 |c 0105 |h 0 | ||
| author_variant |
r r rr |
|---|---|
| matchkey_str |
ruanruyucaoweiyuxulianghua:2020----:uniaiehrceiainfhscltutrocrofbrufc |
| hierarchy_sort_str |
2020transfer abstract |
| bklnumber |
33.06 |
| publishDate |
2020 |
| allfields |
10.1016/j.matdes.2019.108225 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000857.pica (DE-627)ELV048939196 (ELSEVIER)S0264-1275(19)30663-X DE-627 ger DE-627 rakwb eng 380 VZ 610 VZ 530 510 000 VZ 33.06 bkl Ruan, Ruyu verfasserin aut Quantitative characterization of physical structure on carbon fiber surface based on image technique 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness. In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness. Groove size Elsevier Surface physical structure Elsevier Quantitative characterization Elsevier Groove shape Elsevier Surface roughness Elsevier Carbon fiber Elsevier Cao, Weiyu oth Xu, Lianghua oth Enthalten in Elsevier Industrial Tourism: Opportunities for City and Enterprise 2011 s.l. (DE-627)ELV036319309 volume:185 year:2020 day:5 month:01 pages:0 https://doi.org/10.1016/j.matdes.2019.108225 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-MAT 33.06 Mathematische Methoden der Physik VZ AR 185 2020 5 0105 0 |
| spelling |
10.1016/j.matdes.2019.108225 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000857.pica (DE-627)ELV048939196 (ELSEVIER)S0264-1275(19)30663-X DE-627 ger DE-627 rakwb eng 380 VZ 610 VZ 530 510 000 VZ 33.06 bkl Ruan, Ruyu verfasserin aut Quantitative characterization of physical structure on carbon fiber surface based on image technique 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness. In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness. Groove size Elsevier Surface physical structure Elsevier Quantitative characterization Elsevier Groove shape Elsevier Surface roughness Elsevier Carbon fiber Elsevier Cao, Weiyu oth Xu, Lianghua oth Enthalten in Elsevier Industrial Tourism: Opportunities for City and Enterprise 2011 s.l. (DE-627)ELV036319309 volume:185 year:2020 day:5 month:01 pages:0 https://doi.org/10.1016/j.matdes.2019.108225 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-MAT 33.06 Mathematische Methoden der Physik VZ AR 185 2020 5 0105 0 |
| allfields_unstemmed |
10.1016/j.matdes.2019.108225 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000857.pica (DE-627)ELV048939196 (ELSEVIER)S0264-1275(19)30663-X DE-627 ger DE-627 rakwb eng 380 VZ 610 VZ 530 510 000 VZ 33.06 bkl Ruan, Ruyu verfasserin aut Quantitative characterization of physical structure on carbon fiber surface based on image technique 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness. In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness. Groove size Elsevier Surface physical structure Elsevier Quantitative characterization Elsevier Groove shape Elsevier Surface roughness Elsevier Carbon fiber Elsevier Cao, Weiyu oth Xu, Lianghua oth Enthalten in Elsevier Industrial Tourism: Opportunities for City and Enterprise 2011 s.l. (DE-627)ELV036319309 volume:185 year:2020 day:5 month:01 pages:0 https://doi.org/10.1016/j.matdes.2019.108225 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-MAT 33.06 Mathematische Methoden der Physik VZ AR 185 2020 5 0105 0 |
| allfieldsGer |
10.1016/j.matdes.2019.108225 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000857.pica (DE-627)ELV048939196 (ELSEVIER)S0264-1275(19)30663-X DE-627 ger DE-627 rakwb eng 380 VZ 610 VZ 530 510 000 VZ 33.06 bkl Ruan, Ruyu verfasserin aut Quantitative characterization of physical structure on carbon fiber surface based on image technique 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness. In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness. Groove size Elsevier Surface physical structure Elsevier Quantitative characterization Elsevier Groove shape Elsevier Surface roughness Elsevier Carbon fiber Elsevier Cao, Weiyu oth Xu, Lianghua oth Enthalten in Elsevier Industrial Tourism: Opportunities for City and Enterprise 2011 s.l. (DE-627)ELV036319309 volume:185 year:2020 day:5 month:01 pages:0 https://doi.org/10.1016/j.matdes.2019.108225 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-MAT 33.06 Mathematische Methoden der Physik VZ AR 185 2020 5 0105 0 |
| allfieldsSound |
10.1016/j.matdes.2019.108225 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000857.pica (DE-627)ELV048939196 (ELSEVIER)S0264-1275(19)30663-X DE-627 ger DE-627 rakwb eng 380 VZ 610 VZ 530 510 000 VZ 33.06 bkl Ruan, Ruyu verfasserin aut Quantitative characterization of physical structure on carbon fiber surface based on image technique 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness. In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness. Groove size Elsevier Surface physical structure Elsevier Quantitative characterization Elsevier Groove shape Elsevier Surface roughness Elsevier Carbon fiber Elsevier Cao, Weiyu oth Xu, Lianghua oth Enthalten in Elsevier Industrial Tourism: Opportunities for City and Enterprise 2011 s.l. (DE-627)ELV036319309 volume:185 year:2020 day:5 month:01 pages:0 https://doi.org/10.1016/j.matdes.2019.108225 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-MAT 33.06 Mathematische Methoden der Physik VZ AR 185 2020 5 0105 0 |
| language |
English |
| source |
Enthalten in Industrial Tourism: Opportunities for City and Enterprise s.l. volume:185 year:2020 day:5 month:01 pages:0 |
| sourceStr |
Enthalten in Industrial Tourism: Opportunities for City and Enterprise s.l. volume:185 year:2020 day:5 month:01 pages:0 |
| format_phy_str_mv |
Article |
| bklname |
Mathematische Methoden der Physik |
| institution |
findex.gbv.de |
| topic_facet |
Groove size Surface physical structure Quantitative characterization Groove shape Surface roughness Carbon fiber |
| dewey-raw |
380 |
| isfreeaccess_bool |
false |
| container_title |
Industrial Tourism: Opportunities for City and Enterprise |
| authorswithroles_txt_mv |
Ruan, Ruyu @@aut@@ Cao, Weiyu @@oth@@ Xu, Lianghua @@oth@@ |
| publishDateDaySort_date |
2020-01-05T00:00:00Z |
| hierarchy_top_id |
ELV036319309 |
| dewey-sort |
3380 |
| id |
ELV048939196 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV048939196</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230626023116.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">200108s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.matdes.2019.108225</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">/cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000857.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV048939196</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0264-1275(19)30663-X</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">380</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">530</subfield><subfield code="a">510</subfield><subfield code="a">000</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">33.06</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Ruan, Ruyu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Quantitative characterization of physical structure on carbon fiber surface based on image technique</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020transfer abstract</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Groove size</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Surface physical structure</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Quantitative characterization</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Groove shape</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Surface roughness</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Carbon fiber</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Cao, Weiyu</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Xu, Lianghua</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="t">Industrial Tourism: Opportunities for City and Enterprise</subfield><subfield code="d">2011</subfield><subfield code="g">s.l.</subfield><subfield code="w">(DE-627)ELV036319309</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:185</subfield><subfield code="g">year:2020</subfield><subfield code="g">day:5</subfield><subfield code="g">month:01</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.matdes.2019.108225</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-MAT</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">33.06</subfield><subfield code="j">Mathematische Methoden der Physik</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">185</subfield><subfield code="j">2020</subfield><subfield code="b">5</subfield><subfield code="c">0105</subfield><subfield code="h">0</subfield></datafield></record></collection>
|
| author |
Ruan, Ruyu |
| spellingShingle |
Ruan, Ruyu ddc 380 ddc 610 ddc 530 bkl 33.06 Elsevier Groove size Elsevier Surface physical structure Elsevier Quantitative characterization Elsevier Groove shape Elsevier Surface roughness Elsevier Carbon fiber Quantitative characterization of physical structure on carbon fiber surface based on image technique |
| authorStr |
Ruan, Ruyu |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)ELV036319309 |
| format |
electronic Article |
| dewey-ones |
380 - Commerce, communications & transportation 610 - Medicine & health 530 - Physics 510 - Mathematics 000 - Computer science, information & general works |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
elsevier |
| remote_str |
true |
| illustrated |
Not Illustrated |
| topic_title |
380 VZ 610 VZ 530 510 000 VZ 33.06 bkl Quantitative characterization of physical structure on carbon fiber surface based on image technique Groove size Elsevier Surface physical structure Elsevier Quantitative characterization Elsevier Groove shape Elsevier Surface roughness Elsevier Carbon fiber Elsevier |
| topic |
ddc 380 ddc 610 ddc 530 bkl 33.06 Elsevier Groove size Elsevier Surface physical structure Elsevier Quantitative characterization Elsevier Groove shape Elsevier Surface roughness Elsevier Carbon fiber |
| topic_unstemmed |
ddc 380 ddc 610 ddc 530 bkl 33.06 Elsevier Groove size Elsevier Surface physical structure Elsevier Quantitative characterization Elsevier Groove shape Elsevier Surface roughness Elsevier Carbon fiber |
| topic_browse |
ddc 380 ddc 610 ddc 530 bkl 33.06 Elsevier Groove size Elsevier Surface physical structure Elsevier Quantitative characterization Elsevier Groove shape Elsevier Surface roughness Elsevier Carbon fiber |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
zu |
| author2_variant |
w c wc l x lx |
| hierarchy_parent_title |
Industrial Tourism: Opportunities for City and Enterprise |
| hierarchy_parent_id |
ELV036319309 |
| dewey-tens |
380 - Commerce, communications & transportation 610 - Medicine & health 530 - Physics 510 - Mathematics 000 - Computer science, knowledge & systems |
| hierarchy_top_title |
Industrial Tourism: Opportunities for City and Enterprise |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)ELV036319309 |
| title |
Quantitative characterization of physical structure on carbon fiber surface based on image technique |
| ctrlnum |
(DE-627)ELV048939196 (ELSEVIER)S0264-1275(19)30663-X |
| title_full |
Quantitative characterization of physical structure on carbon fiber surface based on image technique |
| author_sort |
Ruan, Ruyu |
| journal |
Industrial Tourism: Opportunities for City and Enterprise |
| journalStr |
Industrial Tourism: Opportunities for City and Enterprise |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
300 - Social sciences 600 - Technology 500 - Science 000 - Computer science, information & general works |
| recordtype |
marc |
| publishDateSort |
2020 |
| contenttype_str_mv |
zzz |
| container_start_page |
0 |
| author_browse |
Ruan, Ruyu |
| container_volume |
185 |
| class |
380 VZ 610 VZ 530 510 000 VZ 33.06 bkl |
| format_se |
Elektronische Aufsätze |
| author-letter |
Ruan, Ruyu |
| doi_str_mv |
10.1016/j.matdes.2019.108225 |
| dewey-full |
380 610 530 510 000 |
| title_sort |
quantitative characterization of physical structure on carbon fiber surface based on image technique |
| title_auth |
Quantitative characterization of physical structure on carbon fiber surface based on image technique |
| abstract |
In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness. |
| abstractGer |
In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness. |
| abstract_unstemmed |
In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness. |
| collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-MAT |
| title_short |
Quantitative characterization of physical structure on carbon fiber surface based on image technique |
| url |
https://doi.org/10.1016/j.matdes.2019.108225 |
| remote_bool |
true |
| author2 |
Cao, Weiyu Xu, Lianghua |
| author2Str |
Cao, Weiyu Xu, Lianghua |
| ppnlink |
ELV036319309 |
| mediatype_str_mv |
z |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| author2_role |
oth oth |
| doi_str |
10.1016/j.matdes.2019.108225 |
| up_date |
2024-07-06T20:11:49.655Z |
| _version_ |
1803861842623201280 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV048939196</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230626023116.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">200108s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.matdes.2019.108225</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">/cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000857.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV048939196</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0264-1275(19)30663-X</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">380</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">530</subfield><subfield code="a">510</subfield><subfield code="a">000</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">33.06</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Ruan, Ruyu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Quantitative characterization of physical structure on carbon fiber surface based on image technique</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020transfer abstract</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">In order to quantitatively characterize the surface physical structure of a bundle of carbon fibers, scanning electron microscope (SEM) was used to photograph the fiber section and edge differential detection method was used to automatically identify the fiber boundary. By finding the smallest circumscribed convex polygon of fiber section and the minimum circumscribed rectangle of grooves though MATLAB, the groove width, depth, contour length and area for 20 monofilaments were calculated. The algorithm was verified by establishing a groove model and used to characterize grooves of three different carbon fibers. The results show quantitative difference of average groove size of three carbon fibers. The distribution of groove size accords with the lognormal distribution, and the fitting degree is between 0.8 and 0.97. The groove shape index rectangularity R and surface roughness Ra of three carbon fibers were also calculated. It indicates that both groove shape and groove size contribute greatly to the fiber surface roughness.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Groove size</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Surface physical structure</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Quantitative characterization</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Groove shape</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Surface roughness</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Carbon fiber</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Cao, Weiyu</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Xu, Lianghua</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="t">Industrial Tourism: Opportunities for City and Enterprise</subfield><subfield code="d">2011</subfield><subfield code="g">s.l.</subfield><subfield code="w">(DE-627)ELV036319309</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:185</subfield><subfield code="g">year:2020</subfield><subfield code="g">day:5</subfield><subfield code="g">month:01</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.matdes.2019.108225</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-MAT</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">33.06</subfield><subfield code="j">Mathematische Methoden der Physik</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">185</subfield><subfield code="j">2020</subfield><subfield code="b">5</subfield><subfield code="c">0105</subfield><subfield code="h">0</subfield></datafield></record></collection>
|
| score |
7.399946 |