The Enfigram: A robust method for extracting repetitive transients in rolling bearing fault diagnosis
•Enfigram is insensitive to accidental shocks or the rotation frequency interference.•The local minimum is used to divide the boundaries in spectrum trend.•The kurtosis of the spectrum of the component envelope spectrum is calculated to evaluate fault information. In the actual industrial production...
Saved in:
| Published in | Mechanical Systems and Signal Processing Vol. 158; p. 107779 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English Japanese |
| Published |
Berlin
Elsevier Ltd
01.09.2021
Elsevier BV |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0888-3270 1096-1216 |
| DOI | 10.1016/j.ymssp.2021.107779 |
Cover
| Abstract | •Enfigram is insensitive to accidental shocks or the rotation frequency interference.•The local minimum is used to divide the boundaries in spectrum trend.•The kurtosis of the spectrum of the component envelope spectrum is calculated to evaluate fault information.
In the actual industrial production, the collected vibration signal often contains accidental impact or harmonic interference due to the influence of mechanical vibration or human interference. However, the current popular Fast Kurtogram (FK) method cannot accurately extract the frequency band with more fault information when processing the signal with such two-type interference. Therefore, this paper proposes a robust method called Enfigram to improve the drawback. In Enfigram method, a new statistical index is designed to select the optimal modulation frequency-band. Envelope Fourier index (Enfi) uses two Fourier transforms to transfer the interference of accidental pulse in the signal envelope to the origin, so that accidental pulse can be eliminated by low-pass filtering. Moreover, the frequency-band segmentation method based on spectrum trend can adaptively divide the fault information into a frequency band in Enfigram, which ensures the integrity of fault information. Compared with FK, Infogram and other methods, the result shows that Enfigram has better performance. |
|---|---|
| AbstractList | In the actual industrial production, the collected vibration signal often contains accidental impact or harmonic interference due to the influence of mechanical vibration or human interference. However, the current popular Fast Kurtogram (FK) method cannot accurately extract the frequency band with more fault information when processing the signal with such two-type interference. Therefore, this paper proposes a robust method called Enfigram to improve the drawback. In Enfigram method, a new statistical index is designed to select the optimal modulation frequency-band. Envelope Fourier index (Enfi) uses two Fourier transforms to transfer the interference of accidental pulse in the signal envelope to the origin, so that accidental pulse can be eliminated by low-pass filtering. Moreover, the frequency-band segmentation method based on spectrum trend can adaptively divide the fault information into a frequency band in Enfigram, which ensures the integrity of fault information. Compared with FK, Infogram and other methods, the result shows that Enfigram has better performance. •Enfigram is insensitive to accidental shocks or the rotation frequency interference.•The local minimum is used to divide the boundaries in spectrum trend.•The kurtosis of the spectrum of the component envelope spectrum is calculated to evaluate fault information. In the actual industrial production, the collected vibration signal often contains accidental impact or harmonic interference due to the influence of mechanical vibration or human interference. However, the current popular Fast Kurtogram (FK) method cannot accurately extract the frequency band with more fault information when processing the signal with such two-type interference. Therefore, this paper proposes a robust method called Enfigram to improve the drawback. In Enfigram method, a new statistical index is designed to select the optimal modulation frequency-band. Envelope Fourier index (Enfi) uses two Fourier transforms to transfer the interference of accidental pulse in the signal envelope to the origin, so that accidental pulse can be eliminated by low-pass filtering. Moreover, the frequency-band segmentation method based on spectrum trend can adaptively divide the fault information into a frequency band in Enfigram, which ensures the integrity of fault information. Compared with FK, Infogram and other methods, the result shows that Enfigram has better performance. |
| ArticleNumber | 107779 |
| Author | Zhang, Kun Deng, Yunjie Xu, Yonggang Ma, Chaoyong |
| Author_xml | – sequence: 1 givenname: Yonggang surname: Xu fullname: Xu, Yonggang organization: Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing 100124, China – sequence: 2 givenname: Yunjie surname: Deng fullname: Deng, Yunjie organization: Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing 100124, China – sequence: 3 givenname: Chaoyong surname: Ma fullname: Ma, Chaoyong organization: Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing 100124, China – sequence: 4 givenname: Kun surname: Zhang fullname: Zhang, Kun email: zkun212@163.com organization: Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing 100124, China |
| BackLink | https://cir.nii.ac.jp/crid/1870302168232196352$$DView record in CiNii |
| BookMark | eNqFkMtq3DAUQEVJoJOkX9CNoN16qoctWYUsQkgfEOgmXQtZvp7cwSNNJU1o_j5y3VUX6UYXLudI4lyQsxADEPKesy1nXH3ab58POR-3ggleN1pr84ZsODOq4YKrM7Jhfd83Umj2llzkvGeMmZapDYGHR6B3YcJdcofP9IamOJxyoQcoj3GkU0wUfpfkfMGwowmOULDgE9C6CxkhlEwxVGueF2AAl5Y5udNc6IhuF2LGfEXOJzdnePd3XpKfX-4ebr819z--fr-9uW98K1RpfCe8mJxx0JlBm8634J0C57RqpVH1y9JxxYZRimEavYFOKC6k8057pTsuL8mH9d5jir9OkIvdx1MK9UlbyZaLnrW6UnKlfIo5J5jsMeHBpWfLmV162r3909MuPe3as1rmH8tjcQVjqClw_o_7cXUDYtWWk_eayYqoXkjBjZKdqNj1ikFt9ISQbPY1sYcRE_hix4ivPvMCOHygGw |
| CitedBy_id | crossref_primary_10_1109_TIM_2024_3412223 crossref_primary_10_1088_1361_6501_ac7bd5 crossref_primary_10_1016_j_anucene_2021_108639 crossref_primary_10_1016_j_ymssp_2021_108366 crossref_primary_10_3390_app13042160 crossref_primary_10_3389_fphy_2023_1199180 crossref_primary_10_1016_j_aei_2024_102731 crossref_primary_10_1016_j_ymssp_2023_110747 crossref_primary_10_3390_ma16093529 crossref_primary_10_1088_1361_6501_ac4a1b crossref_primary_10_1002_acs_3754 crossref_primary_10_1109_TR_2023_3311769 crossref_primary_10_3390_s22239369 crossref_primary_10_1155_2021_8290717 crossref_primary_10_1088_1361_6501_acf0dd crossref_primary_10_1016_j_measurement_2022_110798 crossref_primary_10_1007_s40430_023_04184_z crossref_primary_10_1016_j_ymssp_2021_108751 crossref_primary_10_1109_TMECH_2022_3206435 crossref_primary_10_1016_j_ymssp_2022_109424 crossref_primary_10_1016_j_measurement_2021_110348 crossref_primary_10_1016_j_aei_2024_102487 crossref_primary_10_1016_j_isatra_2023_01_006 crossref_primary_10_1109_TIM_2025_3529067 crossref_primary_10_1007_s12206_022_1107_5 crossref_primary_10_1177_14759217231178653 crossref_primary_10_1088_2631_8695_ad0f79 crossref_primary_10_1007_s11668_022_01406_9 |
| Cites_doi | 10.1088/1361-6501/aafb44 10.1016/j.ymssp.2013.09.015 10.1016/j.ymssp.2015.04.039 10.1016/j.ymssp.2017.12.009 10.1016/j.ymssp.2020.107582 10.1016/j.ymssp.2013.03.021 10.1016/j.ymssp.2004.09.001 10.1016/j.compind.2018.12.013 10.1016/j.ymssp.2004.09.002 10.1016/j.ymssp.2019.05.003 10.1115/1.1379745 10.1016/j.ymssp.2009.06.015 10.1016/j.ndteint.2009.01.009 10.1016/j.ymssp.2015.04.034 10.1016/0022-460X(84)90595-9 10.1016/j.ymssp.2013.05.024 10.1016/j.ymssp.2010.12.008 10.1063/1.3082021 10.1016/j.ymssp.2012.10.003 10.1016/j.ymssp.2010.12.011 10.1016/j.ymssp.2010.05.018 10.1016/j.measurement.2018.12.028 10.1109/ACCESS.2019.2899036 10.3390/app8122352 10.1016/j.ymssp.2005.12.002 10.1016/j.ymssp.2009.02.003 10.1016/j.ymssp.2010.07.017 10.1109/TSP.2013.2265222 |
| ContentType | Journal Article |
| Copyright | 2021 Elsevier Ltd Copyright Elsevier BV Sep 2021 |
| Copyright_xml | – notice: 2021 Elsevier Ltd – notice: Copyright Elsevier BV Sep 2021 |
| DBID | RYH AAYXX CITATION 7SC 7SP 8FD JQ2 L7M L~C L~D |
| DOI | 10.1016/j.ymssp.2021.107779 |
| DatabaseName | CiNii Complete CrossRef Computer and Information Systems Abstracts Electronics & Communications Abstracts Technology Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional |
| DatabaseTitle | CrossRef Technology Research Database Computer and Information Systems Abstracts – Academic Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Professional |
| DatabaseTitleList | Technology Research Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| EISSN | 1096-1216 |
| ExternalDocumentID | 10_1016_j_ymssp_2021_107779 S0888327021001746 |
| GroupedDBID | --K --M .~1 0R~ 1B1 1~. 1~5 29M 4.4 457 4G. 5GY 5VS 7-5 71M 8P~ 9JN AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AAXUO AAYFN ABBOA ABEFU ABFNM ABJNI ABMAC ABXDB ABYKQ ACDAQ ACGFS ACNNM ACRLP ACZNC ADBBV ADEZE ADFGL ADJOM ADMUD ADTZH AEBSH AECPX AEKER AENEX AFKWA AFTJW AGHFR AGUBO AGYEJ AHHHB AHJVU AHZHX AIALX AIEXJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD ASPBG AVWKF AXJTR AZFZN BJAXD BKOJK BLXMC CAG COF CS3 DM4 DU5 EBS EFBJH EFLBG EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-2 G-Q G8K GBLVA GBOLZ HLZ HVGLF HZ~ IHE J1W JJJVA KOM LG5 LG9 LY7 M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- RIG ROL RPZ SBC SDF SDG SDP SES SET SEW SPC SPCBC SPD SST SSV SSZ T5K WUQ XPP ZMT ZU3 ~G- AATTM AAXKI AAYWO ACVFH ADCNI AEIPS AEUPX AFPUW AFXIZ AGCQF AGRNS AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP BNPGV RYH SSH AAYXX ABDPE ABWVN ACRPL ADNMO AFJKZ AGQPQ CITATION 7SC 7SP 8FD EFKBS JQ2 L7M L~C L~D |
| ID | FETCH-LOGICAL-c426t-c52c2fa9ae59b795c4eca6eaa7643960943a160bd32bfdc9e526123aca7c67513 |
| IEDL.DBID | AIKHN |
| ISSN | 0888-3270 |
| IngestDate | Sun Jul 13 04:42:15 EDT 2025 Thu Apr 24 22:56:42 EDT 2025 Tue Jul 01 04:30:09 EDT 2025 Thu Jun 26 22:57:39 EDT 2025 Fri Feb 23 02:46:08 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Fault diagnosis Optimal frequency-band extraction Enfigram Robust Accidental pulse |
| Language | English Japanese |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c426t-c52c2fa9ae59b795c4eca6eaa7643960943a160bd32bfdc9e526123aca7c67513 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ORCID | 0000-0002-3513-8988 0000-0002-2206-8968 0000-0001-9109-891X |
| PQID | 2614128047 |
| PQPubID | 2045429 |
| ParticipantIDs | proquest_journals_2614128047 crossref_primary_10_1016_j_ymssp_2021_107779 crossref_citationtrail_10_1016_j_ymssp_2021_107779 nii_cinii_1870302168232196352 elsevier_sciencedirect_doi_10_1016_j_ymssp_2021_107779 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | September 2021 2021-09-01 2021-09-00 20210901 |
| PublicationDateYYYYMMDD | 2021-09-01 |
| PublicationDate_xml | – month: 09 year: 2021 text: September 2021 |
| PublicationDecade | 2020 |
| PublicationPlace | Berlin |
| PublicationPlace_xml | – name: Berlin |
| PublicationTitle | Mechanical Systems and Signal Processing |
| PublicationYear | 2021 |
| Publisher | Elsevier Ltd Elsevier BV |
| Publisher_xml | – name: Elsevier Ltd – name: Elsevier BV |
| References | Antoni (b0060) 2006; 20 Cui, Wang, Xu, Jiang, Zhou (b0005) 2019; 135 Zhang, Randall (b0075) 2009; 23 Moshrefzadeh, Fasana (b0135) 2018; 105 Antoni (b0130) 2016; 74 Gilles (b0140) 2013; 61 McFadden, Smith (b0050) 1984; 96 Wang, Li, Song, Cui (b0015) 2019; 105 Xu, Zhang, Ma, Cui, Tian (b0010) 2019; 130 Wang, Liang (b0085) 2011; 25 Liang, Lei, Que (b0110) 2008; 79 Barszcz, JabŁoński (b0115) 2011; 25 Dwyer (b0055) 1983 Cui, Wang, Wang, Wu (b0030) 2019; 7 Chen, Li, Li, Huang (b0125) 2009; 80 Chen, Zhang, Zi, He, Sun (b0100) 2013; 40 Wang, He, Zi (b0080) 2010; 24 Xu, Tian, Zhang, Ma (b0025) 2019; 30 Wang, Xiang, Markert, Liang (b0150) 2016; 66–67 Sun, He, Zi, Yuan, Wang, Chen, He (b0105) 2014; 43 Tse, Wang (b0035) 2013; 40 Lei, Lin, He, Zi (b0090) 2011; 25 Liang, Huang, Que (b0120) 2009; 42 Zhang, Xu, Liao, Song, Chen (b0020) 2021; 154 Wang, Tse, Tsui (b0095) 2013; 35 Xu, Zhang, Ma, Li, Zhang (b0145) 2018; 8 Antoni, Randall (b0065) 2006; 20 Tse, Peng, Yam (b0045) 2001; 123 Randall, Antoni (b0040) 2011; 25 Antoni (b0070) 2007; 21 Barszcz (10.1016/j.ymssp.2021.107779_b0115) 2011; 25 Antoni (10.1016/j.ymssp.2021.107779_b0065) 2006; 20 Xu (10.1016/j.ymssp.2021.107779_b0145) 2018; 8 Wang (10.1016/j.ymssp.2021.107779_b0080) 2010; 24 Liang (10.1016/j.ymssp.2021.107779_b0120) 2009; 42 Wang (10.1016/j.ymssp.2021.107779_b0085) 2011; 25 Moshrefzadeh (10.1016/j.ymssp.2021.107779_b0135) 2018; 105 Sun (10.1016/j.ymssp.2021.107779_b0105) 2014; 43 Dwyer (10.1016/j.ymssp.2021.107779_b0055) 1983 Antoni (10.1016/j.ymssp.2021.107779_b0060) 2006; 20 Tse (10.1016/j.ymssp.2021.107779_b0035) 2013; 40 Zhang (10.1016/j.ymssp.2021.107779_b0020) 2021; 154 Chen (10.1016/j.ymssp.2021.107779_b0100) 2013; 40 Xu (10.1016/j.ymssp.2021.107779_b0025) 2019; 30 Tse (10.1016/j.ymssp.2021.107779_b0045) 2001; 123 Wang (10.1016/j.ymssp.2021.107779_b0150) 2016; 66–67 Chen (10.1016/j.ymssp.2021.107779_b0125) 2009; 80 Randall (10.1016/j.ymssp.2021.107779_b0040) 2011; 25 Xu (10.1016/j.ymssp.2021.107779_b0010) 2019; 130 Antoni (10.1016/j.ymssp.2021.107779_b0070) 2007; 21 Lei (10.1016/j.ymssp.2021.107779_b0090) 2011; 25 Antoni (10.1016/j.ymssp.2021.107779_b0130) 2016; 74 Gilles (10.1016/j.ymssp.2021.107779_b0140) 2013; 61 Wang (10.1016/j.ymssp.2021.107779_b0095) 2013; 35 McFadden (10.1016/j.ymssp.2021.107779_b0050) 1984; 96 Zhang (10.1016/j.ymssp.2021.107779_b0075) 2009; 23 Wang (10.1016/j.ymssp.2021.107779_b0015) 2019; 105 Cui (10.1016/j.ymssp.2021.107779_b0030) 2019; 7 Cui (10.1016/j.ymssp.2021.107779_b0005) 2019; 135 Liang (10.1016/j.ymssp.2021.107779_b0110) 2008; 79 |
| References_xml | – volume: 135 start-page: 678 year: 2019 end-page: 684 ident: b0005 article-title: A novel Switching Unscented Kalman Filter method for remaining useful life prediction of rolling bearing publication-title: Measurement – volume: 40 start-page: 499 year: 2013 end-page: 519 ident: b0035 article-title: The design of a new sparsogram for fast bearing fault diagnosis: Part 1 of the two related manuscripts that have a joint title as “Two automatic vibration-based fault diagnostic methods using the novel sparsity measurement publication-title: Mech. Syst. Signal Process. – volume: 35 start-page: 176 year: 2013 end-page: 199 ident: b0095 article-title: An enhanced Kurtogram method for fault diagnosis of rolling element bearings publication-title: Mech. Syst. Sig. Process. – volume: 25 start-page: 431 year: 2011 end-page: 451 ident: b0115 article-title: A novel method for the optimal band selection for vibration signal demodulation and comparison with the Kurtogram publication-title: Mech. Syst. Signal Process. – volume: 25 start-page: 1738 year: 2011 end-page: 1749 ident: b0090 article-title: Application of an improved kurtogram method for fault diagnosis of rolling element bearings publication-title: Mech. Syst. Sig. Process. – volume: 43 start-page: 1 year: 2014 end-page: 24 ident: b0105 article-title: Multiwavelet transform and its applications in mechanical fault diagnosis—a review publication-title: Mech. Syst. Sig. Process. – volume: 25 start-page: 485 year: 2011 end-page: 520 ident: b0040 article-title: Rolling element bearing diagnostics—A tutorial publication-title: Mech. Syst. Signal Process. – volume: 24 start-page: 119 year: 2010 end-page: 137 ident: b0080 article-title: Enhancement of signal denoising and multiple fault signatures detecting in rotating machinery using dual-tree complex wavelet transform publication-title: Mech. Syst. Sig. Process. – volume: 123 start-page: 303 year: 2001 end-page: 310 ident: b0045 article-title: Wavelet analysis and envelope detection for rolling element bearing fault diagnosis – their effectiveness and flexibilities publication-title: J. Vib. Acoust. – volume: 79 start-page: 1 year: 2008 end-page: 6 ident: b0110 article-title: Sparsity enhancement for blind deconvolution of ultrasonic signals in nondestructive testing application publication-title: Rev. Sci. Instrum. – volume: 105 start-page: 182 year: 2019 end-page: 190 ident: b0015 article-title: A novel convolutional neural network based fault recognition method via image fusion of multi-vibration-signals publication-title: Comput. Indust. – volume: 23 start-page: 1509 year: 2009 end-page: 1517 ident: b0075 article-title: Rolling element bearing fault diagnosis based on the combination of genetic algorithms and fast kurtogram publication-title: Mech. Syst. Sig. Process. – volume: 30 start-page: 1 year: 2019 end-page: 19 ident: b0025 article-title: Application of an enhanced fast kurtogram based on empirical wavelet transform for bearing fault diagnosis publication-title: Meas. Sci. Technol. – volume: 40 start-page: 1 year: 2013 end-page: 37 ident: b0100 article-title: Detecting of transient vibration signatures using an improved fast spatial–spectral ensemble kurtosis kurtogram and its applications to mechanical signature analysis of short duration data from rotating machinery publication-title: Mech. Syst. Sig. Process. – volume: 7 start-page: 22710 year: 2019 end-page: 22718 ident: b0030 article-title: Improved fault size estimation method for rolling element bearings based on concatenation dictionary publication-title: IEEE Access – volume: 42 start-page: 430 year: 2009 end-page: 434 ident: b0120 article-title: Sparse deconvolution method for improving the time-resolution of ultrasonic NDE signals publication-title: NDT E Int. – volume: 8 start-page: 1 year: 2018 end-page: 25 ident: b0145 article-title: An improved empirical wavelet transform and its applications in rolling bearing fault diagnosis publication-title: Appl. Sci. – start-page: 607 year: 1983 end-page: 610 ident: b0055 article-title: Detection of non-Gaussian signals by frequency domain kurtosis estimation publication-title: International Conference on Acoustic, Speech, and Signal Processing, Boston – volume: 25 start-page: 1750 year: 2011 end-page: 1764 ident: b0085 article-title: An adaptive SK technique and its application for fault detection of rolling element bearings publication-title: Mech. Syst. Sig. Process. – volume: 130 start-page: 87 year: 2019 end-page: 107 ident: b0010 article-title: Adaptive Kurtogram and its applications in rolling bearing fault diagnosis publication-title: Mech. Syst. Signal Process. – volume: 105 start-page: 294 year: 2018 end-page: 318 ident: b0135 article-title: The Autogram: An effective approach for selecting the optimal demodulation band in rolling element bearings diagnosis publication-title: Mech. Syst. Signal Process. – volume: 20 start-page: 282 year: 2006 end-page: 307 ident: b0060 article-title: The spectral kurtosis: a useful tool for characterising non-stationary signals publication-title: Mech. Syst. Signal Process. – volume: 61 start-page: 3999 year: 2013 end-page: 4010 ident: b0140 article-title: Empirical wavelet transform publication-title: IEEE Trans. Signal Process. – volume: 21 start-page: 108 year: 2007 end-page: 124 ident: b0070 article-title: Fast computation of the kurtogram for the detection of transient faults publication-title: Mech. Syst. Signal Process. – volume: 154 start-page: 107582 year: 2021 ident: b0020 article-title: A novel Fast Entrogram and its applications in rolling bearing fault diagnosis publication-title: Mechanical Systems and Signal Processing – volume: 66–67 start-page: 679 year: 2016 end-page: 698 ident: b0150 article-title: Spectral kurtosis for fault detection, diagnosis and prognostics of rotating machines: A review with applications publication-title: Mech. Syst. Signal Process. – volume: 74 start-page: 73 year: 2016 end-page: 94 ident: b0130 article-title: The infogram: Entropic evidence of the signature of repetitive transients publication-title: Mech. Syst. Signal Process. – volume: 20 start-page: 308 year: 2006 end-page: 331 ident: b0065 article-title: The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines publication-title: Mech. Syst. Signal Process. – volume: 80 start-page: 1 year: 2009 end-page: 7 ident: b0125 article-title: Signal extraction using ensemble empirical mode decomposition and sparsity in pipeline magnetic flux leakage nondestructive evaluation publication-title: Rev. Sci. Instrum. – volume: 96 start-page: 69 year: 1984 end-page: 82 ident: b0050 article-title: Model for the vibration produced by a single point defect in a rolling element bearing publication-title: J. Sound Vib. – volume: 30 start-page: 1 issue: 3 year: 2019 ident: 10.1016/j.ymssp.2021.107779_b0025 article-title: Application of an enhanced fast kurtogram based on empirical wavelet transform for bearing fault diagnosis publication-title: Meas. Sci. Technol. doi: 10.1088/1361-6501/aafb44 – volume: 43 start-page: 1 issue: 1–2 year: 2014 ident: 10.1016/j.ymssp.2021.107779_b0105 article-title: Multiwavelet transform and its applications in mechanical fault diagnosis—a review publication-title: Mech. Syst. Sig. Process. doi: 10.1016/j.ymssp.2013.09.015 – volume: 66–67 start-page: 679 year: 2016 ident: 10.1016/j.ymssp.2021.107779_b0150 article-title: Spectral kurtosis for fault detection, diagnosis and prognostics of rotating machines: A review with applications publication-title: Mech. Syst. Signal Process. doi: 10.1016/j.ymssp.2015.04.039 – volume: 105 start-page: 294 year: 2018 ident: 10.1016/j.ymssp.2021.107779_b0135 article-title: The Autogram: An effective approach for selecting the optimal demodulation band in rolling element bearings diagnosis publication-title: Mech. Syst. Signal Process. doi: 10.1016/j.ymssp.2017.12.009 – volume: 154 start-page: 107582 year: 2021 ident: 10.1016/j.ymssp.2021.107779_b0020 article-title: A novel Fast Entrogram and its applications in rolling bearing fault diagnosis publication-title: Mechanical Systems and Signal Processing doi: 10.1016/j.ymssp.2020.107582 – volume: 40 start-page: 1 issue: 1 year: 2013 ident: 10.1016/j.ymssp.2021.107779_b0100 article-title: Detecting of transient vibration signatures using an improved fast spatial–spectral ensemble kurtosis kurtogram and its applications to mechanical signature analysis of short duration data from rotating machinery publication-title: Mech. Syst. Sig. Process. doi: 10.1016/j.ymssp.2013.03.021 – volume: 20 start-page: 282 issue: 2 year: 2006 ident: 10.1016/j.ymssp.2021.107779_b0060 article-title: The spectral kurtosis: a useful tool for characterising non-stationary signals publication-title: Mech. Syst. Signal Process. doi: 10.1016/j.ymssp.2004.09.001 – volume: 105 start-page: 182 year: 2019 ident: 10.1016/j.ymssp.2021.107779_b0015 article-title: A novel convolutional neural network based fault recognition method via image fusion of multi-vibration-signals publication-title: Comput. Indust. doi: 10.1016/j.compind.2018.12.013 – volume: 20 start-page: 308 year: 2006 ident: 10.1016/j.ymssp.2021.107779_b0065 article-title: The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines publication-title: Mech. Syst. Signal Process. doi: 10.1016/j.ymssp.2004.09.002 – volume: 130 start-page: 87 year: 2019 ident: 10.1016/j.ymssp.2021.107779_b0010 article-title: Adaptive Kurtogram and its applications in rolling bearing fault diagnosis publication-title: Mech. Syst. Signal Process. doi: 10.1016/j.ymssp.2019.05.003 – volume: 123 start-page: 303 year: 2001 ident: 10.1016/j.ymssp.2021.107779_b0045 article-title: Wavelet analysis and envelope detection for rolling element bearing fault diagnosis – their effectiveness and flexibilities publication-title: J. Vib. Acoust. doi: 10.1115/1.1379745 – volume: 24 start-page: 119 issue: 1 year: 2010 ident: 10.1016/j.ymssp.2021.107779_b0080 article-title: Enhancement of signal denoising and multiple fault signatures detecting in rotating machinery using dual-tree complex wavelet transform publication-title: Mech. Syst. Sig. Process. doi: 10.1016/j.ymssp.2009.06.015 – volume: 42 start-page: 430 year: 2009 ident: 10.1016/j.ymssp.2021.107779_b0120 article-title: Sparse deconvolution method for improving the time-resolution of ultrasonic NDE signals publication-title: NDT E Int. doi: 10.1016/j.ndteint.2009.01.009 – volume: 74 start-page: 73 year: 2016 ident: 10.1016/j.ymssp.2021.107779_b0130 article-title: The infogram: Entropic evidence of the signature of repetitive transients publication-title: Mech. Syst. Signal Process. doi: 10.1016/j.ymssp.2015.04.034 – volume: 96 start-page: 69 issue: 1 year: 1984 ident: 10.1016/j.ymssp.2021.107779_b0050 article-title: Model for the vibration produced by a single point defect in a rolling element bearing publication-title: J. Sound Vib. doi: 10.1016/0022-460X(84)90595-9 – volume: 40 start-page: 499 year: 2013 ident: 10.1016/j.ymssp.2021.107779_b0035 article-title: The design of a new sparsogram for fast bearing fault diagnosis: Part 1 of the two related manuscripts that have a joint title as “Two automatic vibration-based fault diagnostic methods using the novel sparsity measurement publication-title: Mech. Syst. Signal Process. doi: 10.1016/j.ymssp.2013.05.024 – volume: 25 start-page: 1750 issue: 5 year: 2011 ident: 10.1016/j.ymssp.2021.107779_b0085 article-title: An adaptive SK technique and its application for fault detection of rolling element bearings publication-title: Mech. Syst. Sig. Process. doi: 10.1016/j.ymssp.2010.12.008 – volume: 80 start-page: 1 year: 2009 ident: 10.1016/j.ymssp.2021.107779_b0125 article-title: Signal extraction using ensemble empirical mode decomposition and sparsity in pipeline magnetic flux leakage nondestructive evaluation publication-title: Rev. Sci. Instrum. doi: 10.1063/1.3082021 – volume: 35 start-page: 176 issue: 1–2 year: 2013 ident: 10.1016/j.ymssp.2021.107779_b0095 article-title: An enhanced Kurtogram method for fault diagnosis of rolling element bearings publication-title: Mech. Syst. Sig. Process. doi: 10.1016/j.ymssp.2012.10.003 – volume: 25 start-page: 1738 issue: 5 year: 2011 ident: 10.1016/j.ymssp.2021.107779_b0090 article-title: Application of an improved kurtogram method for fault diagnosis of rolling element bearings publication-title: Mech. Syst. Sig. Process. doi: 10.1016/j.ymssp.2010.12.011 – volume: 79 start-page: 1 year: 2008 ident: 10.1016/j.ymssp.2021.107779_b0110 article-title: Sparsity enhancement for blind deconvolution of ultrasonic signals in nondestructive testing application publication-title: Rev. Sci. Instrum. – volume: 25 start-page: 431 year: 2011 ident: 10.1016/j.ymssp.2021.107779_b0115 article-title: A novel method for the optimal band selection for vibration signal demodulation and comparison with the Kurtogram publication-title: Mech. Syst. Signal Process. doi: 10.1016/j.ymssp.2010.05.018 – volume: 135 start-page: 678 year: 2019 ident: 10.1016/j.ymssp.2021.107779_b0005 article-title: A novel Switching Unscented Kalman Filter method for remaining useful life prediction of rolling bearing publication-title: Measurement doi: 10.1016/j.measurement.2018.12.028 – volume: 7 start-page: 22710 year: 2019 ident: 10.1016/j.ymssp.2021.107779_b0030 article-title: Improved fault size estimation method for rolling element bearings based on concatenation dictionary publication-title: IEEE Access doi: 10.1109/ACCESS.2019.2899036 – volume: 8 start-page: 1 issue: 12 year: 2018 ident: 10.1016/j.ymssp.2021.107779_b0145 article-title: An improved empirical wavelet transform and its applications in rolling bearing fault diagnosis publication-title: Appl. Sci. doi: 10.3390/app8122352 – volume: 21 start-page: 108 year: 2007 ident: 10.1016/j.ymssp.2021.107779_b0070 article-title: Fast computation of the kurtogram for the detection of transient faults publication-title: Mech. Syst. Signal Process. doi: 10.1016/j.ymssp.2005.12.002 – volume: 23 start-page: 1509 issue: 5 year: 2009 ident: 10.1016/j.ymssp.2021.107779_b0075 article-title: Rolling element bearing fault diagnosis based on the combination of genetic algorithms and fast kurtogram publication-title: Mech. Syst. Sig. Process. doi: 10.1016/j.ymssp.2009.02.003 – volume: 25 start-page: 485 year: 2011 ident: 10.1016/j.ymssp.2021.107779_b0040 article-title: Rolling element bearing diagnostics—A tutorial publication-title: Mech. Syst. Signal Process. doi: 10.1016/j.ymssp.2010.07.017 – start-page: 607 year: 1983 ident: 10.1016/j.ymssp.2021.107779_b0055 article-title: Detection of non-Gaussian signals by frequency domain kurtosis estimation – volume: 61 start-page: 3999 issue: 16 year: 2013 ident: 10.1016/j.ymssp.2021.107779_b0140 article-title: Empirical wavelet transform publication-title: IEEE Trans. Signal Process. doi: 10.1109/TSP.2013.2265222 |
| SSID | ssj0009406 ssib006540756 ssib006540755 |
| Score | 2.4933069 |
| Snippet | •Enfigram is insensitive to accidental shocks or the rotation frequency interference.•The local minimum is used to divide the boundaries in spectrum trend.•The... In the actual industrial production, the collected vibration signal often contains accidental impact or harmonic interference due to the influence of... |
| SourceID | proquest crossref nii elsevier |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 107779 |
| SubjectTerms | Accidental pulse Enfigram Fault diagnosis Fourier transforms Frequencies Interference Low pass filters Optimal frequency-band extraction Robust Robustness Roller bearings Segmentation Signal processing Vibration |
| Title | The Enfigram: A robust method for extracting repetitive transients in rolling bearing fault diagnosis |
| URI | https://dx.doi.org/10.1016/j.ymssp.2021.107779 https://cir.nii.ac.jp/crid/1870302168232196352 https://www.proquest.com/docview/2614128047 |
| Volume | 158 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV07T-QwEB6xS8MVCDjQLS-5oCRs4sROQrdCoAUEDYdEZ9mOg3KCsNpkCxp-OzN58BCI4ppEsTKKNW8rM98AHASB5YmOMy8JnfQi6YRnXI7mLkSWpNZPk2Zaw9W1nN5GF3fibglO-l4YKqvsfH_r0xtv3a2MO26OZ0UxvkH7QHWM6dCCahXJASzzMJViCMuT88vp9Tv2btSM2KT3PSLowYeaMq_nx6oi3Eoe4EocU0nX9wFqUBbFF4fdRKGzNVjt0kc2aXe4Dkuu3IBfH0AFf4NDybPTMi-o7uqYTdj8ySyqmrWzohkmqQwdctMcVd6zuZtRnxn6PFZT2KL2yIoVJVI1aN3MoCnQPdeLh5plbWVeUW3C7dnp35Op1w1T8CwG4dqzglueExa3SE2cChs5q6XTOqacRFKBoQ6kb7KQmzyzqRMELhZqq2OLh4og3IJh-VS6P8BMqBPjMpfzTESScnQr6W9f6EKZON8fAe85qGyHNE4DLx5UX1L2TzVsV8R21bJ9BIdvRLMWaOPn12UvGvVJXxSGgp8J91CQuC-6Bgk5PB7IBBNL8kWCj2C3F7HqzLlSyIoIA7kfxdv_-90dWKGntjxtF4b1fOH2MJ-pzT4Mjl6C_U5rXwHpPvJ8 |
| linkProvider | Elsevier |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Lb9QwEB615QAcEE-xfYAPHAmbOH4k3Kqq1QJtL7RSb5btOChVSVeb7IFLf3tnnIQWgXrgkkiJrVgz45mx8s03AB-yzPPC6iop8qASoYJMXKhxu0tZFaVPyyJ2azg5VYtz8fVCXmzAwVQLQ7DK0fcPPj166_HJfJTmfNk08--4P9AcNR1a0KyE2oRHQuaacH2fbu5wHqWIDTZpdELDJ-qhCPL69bPriLWSZ_hEawJ0_Ts8bbZN85e7jjHo6Dk8G5NHtj-s7wVshPYlPL1HKfgKAuqdHbZ1Q6irz2yfra7duuvZ0CmaYYrK0B3H0qj2B1uFJVWZocdjPQUtKo7sWNPirMjVzRxuBLrXdn3Vs2rA5TXdazg_Ojw7WCRjK4XEYwjuEy-55zUxccvS6VJ6EbxVwVpNGYkieKHNVOqqnLu68mWQRC2WW2-1xyNFlr-Brfa6DW-BudwWLlSh5pUUijJ0r-hfXx5yVYQ0nQGfJGj8yDNO7S6uzAQouzRR7IbEbgaxz-Dj70nLgWbj4eFqUo35w1oMBoKHJ-6hInFddM0Kcnc8UwWmleSJJJ_B7qRiM27mzqAoBIbxVOjt__3ue3i8ODs5NsdfTr_twBN6MwDVdmGrX63DHmY2vXsXLfcW8vvzRw |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=The+Enfigram%3A+A+robust+method+for+extracting+repetitive+transients+in+rolling+bearing+fault+diagnosis&rft.jtitle=Mechanical+Systems+and+Signal+Processing&rft.au=Yonggang+Xu&rft.au=Chaoyong+Ma&rft.au=Yunjie+Deng&rft.au=Kun+Zhang&rft.date=2021-09-01&rft.pub=Elsevier+BV&rft.issn=0888-3270&rft.volume=158&rft.spage=107779&rft_id=info:doi/10.1016%2Fj.ymssp.2021.107779 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0888-3270&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0888-3270&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0888-3270&client=summon |