The monitoring of flank wear on the CBN tool in the hard turning process View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2003-11

AUTHORS

J. M. Zhou, M. Andersson, J. E. Stahl

ABSTRACT

In precision hard turning, tool flank wear is one of the major factors contributing to the geometric error and thermal damage in a machined workpiece. Tool wear not only directly reduces the part geometry accuracy but also increases the cutting forces drastically. The change in cutting forces causes instability in the tool motion, and in turn, more inaccuracy. There are demands for reliably monitoring the progress of tool wear during a machining process to provide information for both correction of geometric errors and to guarantee the surface integrity of the workpiece. A new method for tool wear monitoring in precision hard turning is presented in this paper. The flank wear of a CBN tool is monitored by feature parameters extracted from the measured passive force, by the use of a force dynamometer. The feature parameters include the passive force level, the frequency energy and the accumulated cutting time. An ANN model was used to integrate these feature parameters in order to obtain more reliable and robust flank wear monitoring. Finally, the results from validation tests indicate that the developed monitoring system is robust and consistent for tool wear monitoring in precision hard turning. More... »

PAGES

697-702

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00170-003-1569-2

DOI

http://dx.doi.org/10.1007/s00170-003-1569-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1038552028


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0910", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Manufacturing Engineering", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/09", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Engineering", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Lund University", 
          "id": "https://www.grid.ac/institutes/grid.4514.4", 
          "name": [
            "Department of Mechanical Engineering, Lund University, 221 00, Lund, Sweden"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhou", 
        "givenName": "J. M.", 
        "id": "sg:person.016375551125.20", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016375551125.20"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Lund University", 
          "id": "https://www.grid.ac/institutes/grid.4514.4", 
          "name": [
            "Department of Mechanical Engineering, Lund University, 221 00, Lund, Sweden"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Andersson", 
        "givenName": "M.", 
        "id": "sg:person.014320503475.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014320503475.27"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Lund University", 
          "id": "https://www.grid.ac/institutes/grid.4514.4", 
          "name": [
            "Department of Mechanical Engineering, Lund University, 221 00, Lund, Sweden"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Stahl", 
        "givenName": "J. E.", 
        "id": "sg:person.011221224553.93", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011221224553.93"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/s0043-1648(97)00139-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042732732"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2003-11", 
    "datePublishedReg": "2003-11-01", 
    "description": "In precision hard turning, tool flank wear is one of the major factors contributing to the geometric error and thermal damage in a machined workpiece. Tool wear not only directly reduces the part geometry accuracy but also increases the cutting forces drastically. The change in cutting forces causes instability in the tool motion, and in turn, more inaccuracy. There are demands for reliably monitoring the progress of tool wear during a machining process to provide information for both correction of geometric errors and to guarantee the surface integrity of the workpiece. A new method for tool wear monitoring in precision hard turning is presented in this paper. The flank wear of a CBN tool is monitored by feature parameters extracted from the measured passive force, by the use of a force dynamometer. The feature parameters include the passive force level, the frequency energy and the accumulated cutting time. An ANN model was used to integrate these feature parameters in order to obtain more reliable and robust flank wear monitoring. Finally, the results from validation tests indicate that the developed monitoring system is robust and consistent for tool wear monitoring in precision hard turning.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s00170-003-1569-2", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1043671", 
        "issn": [
          "0268-3768", 
          "1433-3015"
        ], 
        "name": "The International Journal of Advanced Manufacturing Technology", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "9-10", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "22"
      }
    ], 
    "name": "The monitoring of flank wear on the CBN tool in the hard turning process", 
    "pagination": "697-702", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "b7a56d7bbb9be49cd9ee6e682147541ea9a756086dc835e7ebae6539815a76c5"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s00170-003-1569-2"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1038552028"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s00170-003-1569-2", 
      "https://app.dimensions.ai/details/publication/pub.1038552028"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T19:50", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8681_00000482.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007/s00170-003-1569-2"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s00170-003-1569-2'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00170-003-1569-2'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00170-003-1569-2'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00170-003-1569-2'


 

This table displays all metadata directly associated to this object as RDF triples.

78 TRIPLES      21 PREDICATES      28 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s00170-003-1569-2 schema:about anzsrc-for:09
2 anzsrc-for:0910
3 schema:author Nc15edd2f69ab4003b42db3dc7c1bf9f4
4 schema:citation https://doi.org/10.1016/s0043-1648(97)00139-7
5 schema:datePublished 2003-11
6 schema:datePublishedReg 2003-11-01
7 schema:description In precision hard turning, tool flank wear is one of the major factors contributing to the geometric error and thermal damage in a machined workpiece. Tool wear not only directly reduces the part geometry accuracy but also increases the cutting forces drastically. The change in cutting forces causes instability in the tool motion, and in turn, more inaccuracy. There are demands for reliably monitoring the progress of tool wear during a machining process to provide information for both correction of geometric errors and to guarantee the surface integrity of the workpiece. A new method for tool wear monitoring in precision hard turning is presented in this paper. The flank wear of a CBN tool is monitored by feature parameters extracted from the measured passive force, by the use of a force dynamometer. The feature parameters include the passive force level, the frequency energy and the accumulated cutting time. An ANN model was used to integrate these feature parameters in order to obtain more reliable and robust flank wear monitoring. Finally, the results from validation tests indicate that the developed monitoring system is robust and consistent for tool wear monitoring in precision hard turning.
8 schema:genre research_article
9 schema:inLanguage en
10 schema:isAccessibleForFree false
11 schema:isPartOf N8a941472462d494aa9b51611afea73f3
12 Ncc98b4111d58407483ebbf6e45704a3a
13 sg:journal.1043671
14 schema:name The monitoring of flank wear on the CBN tool in the hard turning process
15 schema:pagination 697-702
16 schema:productId N2a1f919bf7ef4e9aa7425d9122d951c2
17 Nc4772ed4c7a84c73a8479f17de2af339
18 Nf5b52707eb154520ba2ec62f36e8a188
19 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038552028
20 https://doi.org/10.1007/s00170-003-1569-2
21 schema:sdDatePublished 2019-04-10T19:50
22 schema:sdLicense https://scigraph.springernature.com/explorer/license/
23 schema:sdPublisher N77181a68729841c8bc37b70b18ab4ddc
24 schema:url http://link.springer.com/10.1007/s00170-003-1569-2
25 sgo:license sg:explorer/license/
26 sgo:sdDataset articles
27 rdf:type schema:ScholarlyArticle
28 N2a1f919bf7ef4e9aa7425d9122d951c2 schema:name dimensions_id
29 schema:value pub.1038552028
30 rdf:type schema:PropertyValue
31 N681fe3d98a474668980e92191ef32956 rdf:first sg:person.011221224553.93
32 rdf:rest rdf:nil
33 N77181a68729841c8bc37b70b18ab4ddc schema:name Springer Nature - SN SciGraph project
34 rdf:type schema:Organization
35 N8a941472462d494aa9b51611afea73f3 schema:issueNumber 9-10
36 rdf:type schema:PublicationIssue
37 Nc15edd2f69ab4003b42db3dc7c1bf9f4 rdf:first sg:person.016375551125.20
38 rdf:rest Nf455213c05244f5180c4c05c020db16d
39 Nc4772ed4c7a84c73a8479f17de2af339 schema:name doi
40 schema:value 10.1007/s00170-003-1569-2
41 rdf:type schema:PropertyValue
42 Ncc98b4111d58407483ebbf6e45704a3a schema:volumeNumber 22
43 rdf:type schema:PublicationVolume
44 Nf455213c05244f5180c4c05c020db16d rdf:first sg:person.014320503475.27
45 rdf:rest N681fe3d98a474668980e92191ef32956
46 Nf5b52707eb154520ba2ec62f36e8a188 schema:name readcube_id
47 schema:value b7a56d7bbb9be49cd9ee6e682147541ea9a756086dc835e7ebae6539815a76c5
48 rdf:type schema:PropertyValue
49 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
50 schema:name Engineering
51 rdf:type schema:DefinedTerm
52 anzsrc-for:0910 schema:inDefinedTermSet anzsrc-for:
53 schema:name Manufacturing Engineering
54 rdf:type schema:DefinedTerm
55 sg:journal.1043671 schema:issn 0268-3768
56 1433-3015
57 schema:name The International Journal of Advanced Manufacturing Technology
58 rdf:type schema:Periodical
59 sg:person.011221224553.93 schema:affiliation https://www.grid.ac/institutes/grid.4514.4
60 schema:familyName Stahl
61 schema:givenName J. E.
62 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011221224553.93
63 rdf:type schema:Person
64 sg:person.014320503475.27 schema:affiliation https://www.grid.ac/institutes/grid.4514.4
65 schema:familyName Andersson
66 schema:givenName M.
67 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014320503475.27
68 rdf:type schema:Person
69 sg:person.016375551125.20 schema:affiliation https://www.grid.ac/institutes/grid.4514.4
70 schema:familyName Zhou
71 schema:givenName J. M.
72 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016375551125.20
73 rdf:type schema:Person
74 https://doi.org/10.1016/s0043-1648(97)00139-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042732732
75 rdf:type schema:CreativeWork
76 https://www.grid.ac/institutes/grid.4514.4 schema:alternateName Lund University
77 schema:name Department of Mechanical Engineering, Lund University, 221 00, Lund, Sweden
78 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...