{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T07:34:55Z","timestamp":1761896095598},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2015,7,10]],"date-time":"2015-07-10T00:00:00Z","timestamp":1436486400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"National Key Basic Research Program of China (973 Program)","award":["No. 2014CB049500"],"award-info":[{"award-number":["No. 2014CB049500"]}]},{"name":"Key Technologies R&D Program of Anhui Province","award":["No. 1301021005"],"award-info":[{"award-number":["No. 1301021005"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Intell Manuf"],"published-print":{"date-parts":[[2018,2]]},"DOI":"10.1007\/s10845-015-1125-6","type":"journal-article","created":{"date-parts":[[2015,7,9]],"date-time":"2015-07-09T08:49:27Z","timestamp":1436431767000},"page":"463-480","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Fault feature enhancement for rotating machinery based on quality factor analysis and manifold learning"],"prefix":"10.1007","volume":"29","author":[{"given":"Meng","family":"Gan","sequence":"first","affiliation":[]},{"given":"Cong","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Chang\u2019an","family":"Zhu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2015,7,10]]},"reference":[{"issue":"9","key":"1125_CR1","doi-asserted-by":"crossref","first-page":"2345","DOI":"10.1109\/TIP.2010.2047910","volume":"19","author":"MV Afonso","year":"2010","unstructured":"Afonso, M. V., Bioucas-Dias, J. M., & Figueiredo, M. A. T. (2010). Fast image recovery using variable splitting and constrained optimization. IEEE Transactions on Image Processing, 19(9), 2345\u20132356.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"6","key":"1125_CR2","doi-asserted-by":"crossref","first-page":"1091","DOI":"10.1006\/mssp.2000.1338","volume":"15","author":"N Baydar","year":"2001","unstructured":"Baydar, N., & Ball, A. (2001). A comparative study of acoustic and vibration signals in detection of gear failures using Wigner\u2013Ville distribution. Mechanical Systems and Signal Processing, 15(6), 1091\u20131107.","journal-title":"Mechanical Systems and Signal Processing"},{"issue":"6","key":"1125_CR3","doi-asserted-by":"crossref","first-page":"1373","DOI":"10.1162\/089976603321780317","volume":"15","author":"M Belkin","year":"2003","unstructured":"Belkin, M., & Niyogi, P. (2003). Laplacian eigenmaps for dimensionality reduction and data representation. Neural Computation, 15(6), 1373\u20131396.","journal-title":"Neural Computation"},{"issue":"2","key":"1125_CR4","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1007\/s10845-013-0774-6","volume":"26","author":"T Benkedjouh","year":"2015","unstructured":"Benkedjouh, T., Medjaher, K., Zerhouni, N., & Rechak, S. (2015). Health assessment and life prediction of cutting tools based on support vector regression. Journal of Intelligent Manufacturing, 26(2), 213\u2013223.","journal-title":"Journal of Intelligent Manufacturing"},{"issue":"7","key":"1125_CR5","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1109\/LSP.2006.873141","volume":"13","author":"J Bobin","year":"2008","unstructured":"Bobin, J., Moudden, Y., Starck, J. L., & Elad, M. (2008). Morphological diversity and source separation. IEEE Signal Processing Letters, 13(7), 409\u2013412.","journal-title":"IEEE Signal Processing Letters"},{"issue":"11","key":"1125_CR6","doi-asserted-by":"crossref","first-page":"2675","DOI":"10.1109\/TIP.2007.907073","volume":"16","author":"J Bobin","year":"2007","unstructured":"Bobin, J., Starck, J. L., Fadili, J. M., Moudden, Y., & Donoho, D. L. (2007). Morphological component analysis: An adaptive thresholding strategy. IEEE Transactions on Image Processing, 16(11), 2675\u20132681.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"1\u20132","key":"1125_CR7","first-page":"34","volume":"41","author":"GG Cai","year":"2013","unstructured":"Cai, G. G., Chen, X. F., & He, Z. J. (2013). Sparsity-enabled signal decomposition using tunable Q-factor wavelet transform for fault feature extraction of gearbox. Mechanical Systems and Signal Processing, 41(1\u20132), 34\u201353.","journal-title":"Mechanical Systems and Signal Processing"},{"issue":"1\u20132","key":"1125_CR8","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/S0167-2789(97)00118-8","volume":"110","author":"LY Cao","year":"1997","unstructured":"Cao, L. Y. (1997). Practical method for determining the minimum embedding dimension of a scalar time series. Physica D, 110(1\u20132), 43\u201350.","journal-title":"Physica D"},{"issue":"5","key":"1125_CR9","doi-asserted-by":"crossref","first-page":"961","DOI":"10.1109\/18.57199","volume":"36","author":"I Daubechies","year":"1990","unstructured":"Daubechies, I. (1990). The wavelet transform, time-frequency localization and signal analysis. IEEE Transactions on Information Theory, 36(5), 961\u20131005.","journal-title":"IEEE Transactions on Information Theory"},{"issue":"3","key":"1125_CR10","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1007\/s10845-012-0698-6","volume":"25","author":"BH Freyer","year":"2014","unstructured":"Freyer, B. H., Heyns, P. S., & Theron, N. J. (2014). Comparing orthogonal force and unidirectional strain component processing for tool condition monitoring. Journal of Intelligent Manufacturing, 25(3), 473\u2013487.","journal-title":"Journal of Intelligent Manufacturing"},{"issue":"5","key":"1125_CR11","doi-asserted-by":"crossref","first-page":"1218","DOI":"10.1109\/TIM.2012.2183402","volume":"61","author":"QB He","year":"2012","unstructured":"He, Q. B., Liu, Y. B., Long, Q., & Wang, J. (2012). Time-frequency manifold as a signature for machine health diagnosis. IEEE Transactions on Instrumentation and Measurement, 61(5), 1218\u20131230.","journal-title":"IEEE Transactions on Instrumentation and Measurement"},{"key":"1125_CR12","doi-asserted-by":"crossref","unstructured":"Huang, N. E., Shen, Z., Long, S. R., Wu, M. L. C., Shih, H. H., Zheng, Q. N., et al. (1998). The empirical mode decomposition and the hilbert spectrum for nonlinear and non-stationary time series analysis. In Proceedings of the royal society of London series a: Mathematical physical and engineering sciences (Vol. 454, No. 1971, pp. 903\u2013995).","DOI":"10.1098\/rspa.1998.0193"},{"key":"1125_CR13","unstructured":"Huo, X., Ni, X. S., & Smith, A. K. (2007). A survey of manifold-based learning methods. In T. W. Liao & E. Triantaphyllo (Eds.), Recent advances in data mining of enterprise data.. Singapore: World Scientific."},{"key":"1125_CR14","doi-asserted-by":"crossref","unstructured":"Islam, M. M., Islam, M. N., Asari, V. K., & Karim, M. A. (2012). A new manifold learning technique for face recognition. In Wireless networks and computational intelligence, ICIP (Vol. 292, pp. 282\u2013286).","DOI":"10.1007\/978-3-642-31686-9_33"},{"issue":"3","key":"1125_CR15","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1007\/s10845-012-0706-x","volume":"25","author":"Z Jakovljevic","year":"2014","unstructured":"Jakovljevic, Z., Petrovic, P. B., Mikovic, V. D., & Pajic, M. (2014). Fuzzy inference mechanism for recognition of contact states in intelligent robotic assembly. Journal of Intelligent Manufacturing, 25(3), 571\u2013587.","journal-title":"Journal of Intelligent Manufacturing"},{"issue":"1\u20132","key":"1125_CR16","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.ymssp.2012.09.015","volume":"35","author":"YG Lei","year":"2013","unstructured":"Lei, Y. G., Lin, J., He, Z. J., & Zuo, M. J. (2013). A review on empirical mode decomposition in fault diagnosis of rotating machinery. Mechanical Systems and Signal Processing, 35(1\u20132), 108\u2013126.","journal-title":"Mechanical Systems and Signal Processing"},{"issue":"1","key":"1125_CR17","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1007\/s10845-013-0772-8","volume":"26","author":"HK Li","year":"2015","unstructured":"Li, H. K., Lian, X. T., Guo, C., & Zhao, P. S. (2015). Investigation on early fault classification for rolling element bearing based on the optimal frequency band determination. Journal of Intelligent Manufacturing, 26(1), 189\u2013198.","journal-title":"Journal of Intelligent Manufacturing"},{"key":"1125_CR18","doi-asserted-by":"crossref","unstructured":"Liou, C.\u00a0Y., & Cheng, W.\u00a0C. (2008) Manifold training technique to reconstruct high dynamic range image. In Advances in Neural Networks\u2014ISNN 2008, Pt 2, Proceedings 5 (Vol. 264, pp. 402\u2013409).","DOI":"10.1007\/978-3-540-87734-9_46"},{"issue":"3","key":"1125_CR19","doi-asserted-by":"crossref","first-page":"419","DOI":"10.3901\/CJME.2009.03.419","volume":"22","author":"YF Mao","year":"2009","unstructured":"Mao, Y. F., Qin, S. R., & Qin, Y. (2009). Demodulation based on harmonic wavelet and its application into rotary machinery fault diagnosis. Chinese Journal of Mechanical Engineering, 22(3), 419\u2013425.","journal-title":"Chinese Journal of Mechanical Engineering"},{"issue":"6","key":"1125_CR20","doi-asserted-by":"crossref","first-page":"1429","DOI":"10.1007\/s10845-013-0750-1","volume":"25","author":"MA Mortada","year":"2014","unstructured":"Mortada, M. A., Yacout, S., & Lakis, A. (2014). Fault diagnosis in power transformers using multi-class logical analysis of data. Journal of Intelligent Manufacturing, 25(6), 1429\u20131439.","journal-title":"Journal of Intelligent Manufacturing"},{"issue":"4","key":"1125_CR21","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1093\/comjnl\/7.4.308","volume":"7","author":"JA Nelder","year":"1965","unstructured":"Nelder, J. A., & Mead, R. (1965). A simplex-method for function minimization. Computer Journal, 7(4), 308\u2013313.","journal-title":"Computer Journal"},{"issue":"1","key":"1125_CR22","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1109\/TASSP.1980.1163359","volume":"28","author":"MR Portnoff","year":"1980","unstructured":"Portnoff, M. R. (1980). Time-frequency representation of digital signals and systems based on short-time fourier-analysis. IEEE Transactions on Acoustics Speech and Signal Processing, 28(1), 55\u201369.","journal-title":"IEEE Transactions on Acoustics Speech and Signal Processing"},{"issue":"5500","key":"1125_CR23","doi-asserted-by":"crossref","first-page":"2323","DOI":"10.1126\/science.290.5500.2323","volume":"290","author":"ST Roweis","year":"2000","unstructured":"Roweis, S. T., & Saul, L. K. (2000). Nonlinear dimensionality reduction by locally linear embedding. Science, 290(5500), 2323\u20132326.","journal-title":"Science"},{"issue":"12","key":"1125_CR24","doi-asserted-by":"crossref","first-page":"2793","DOI":"10.1016\/j.sigpro.2010.10.018","volume":"91","author":"IW Selesnick","year":"2011","unstructured":"Selesnick, I. W. (2011). Resonance-based signal decomposition: A new sparsity-enabled signal analysis method. Signal Processing, 91(12), 2793\u20132809.","journal-title":"Signal Processing"},{"issue":"8","key":"1125_CR25","doi-asserted-by":"crossref","first-page":"3560","DOI":"10.1109\/TSP.2011.2143711","volume":"59","author":"IW Selesnick","year":"2011","unstructured":"Selesnick, I. W. (2011). Wavelet transform with tunable Q-factor. IEEE Transactions on Signal Processing, 59(8), 3560\u20133575.","journal-title":"IEEE Transactions on Signal Processing"},{"issue":"1","key":"1125_CR26","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/S0888-3270(03)00046-3","volume":"18","author":"YT Sheen","year":"2004","unstructured":"Sheen, Y. T., & Hung, C. K. (2004). Constructing a wavelet-based envelope function for vibration signal analysis. Mechanical Systems and Signal Processing, 18(1), 119\u2013126.","journal-title":"Mechanical Systems and Signal Processing"},{"key":"1125_CR27","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.neucom.2012.08.070","volume":"124","author":"SL Sun","year":"2014","unstructured":"Sun, S. L., Hussain, Z., & Shawe-Taylor, J. (2014). Manifold-preserving graph reduction for sparse semi-supervised learning. Neurocomputing, 124, 13\u201321.","journal-title":"Neurocomputing"},{"key":"1125_CR28","doi-asserted-by":"crossref","unstructured":"Takens, F. (1981). Detecting strange attractors in turbulence. In Rand, D. A. & Young, L. S. (Eds.), Dynamical systems andturbulence. Lecture notes in mathematics (Vol. 898, pp. 366\u2013381). Berlin: Springer-Verlag","DOI":"10.1007\/BFb0091924"},{"issue":"5500","key":"1125_CR29","doi-asserted-by":"crossref","first-page":"2319","DOI":"10.1126\/science.290.5500.2319","volume":"290","author":"JB Tenenbaum","year":"2000","unstructured":"Tenenbaum, J. B., de Silva, V., & Langford, J. C. (2000). A global geometric framework for nonlinear dimensionality reduction. Science, 290(5500), 2319\u20132323.","journal-title":"Science"},{"key":"1125_CR30","doi-asserted-by":"crossref","unstructured":"Tunc, B., & Gokmen, M. (2011). Manifold learning for face recognition under changing illumination. Telecommunication Systems, 47(3\u20134), 185\u2013195.","DOI":"10.1007\/s11235-010-9311-5"},{"issue":"11","key":"1125_CR31","doi-asserted-by":"crossref","first-page":"2450","DOI":"10.1016\/j.jsv.2014.01.006","volume":"333","author":"J Wang","year":"2014","unstructured":"Wang, J., & He, Q. B. (2014). Exchanged ridge demodulation of time-scale manifold for enhanced fault diagnosis of rotating machinery. Journal of Sound and Vibration, 333(11), 2450\u20132464.","journal-title":"Journal of Sound and Vibration"},{"issue":"1","key":"1125_CR32","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1016\/j.ymssp.2013.03.007","volume":"40","author":"J Wang","year":"2013","unstructured":"Wang, J., He, Q. B., & Kong, F. R. (2013). Automatic fault diagnosis of rotating machines by time-scale manifold ridge analysis. Mechanical Systems and Signal Processing, 40(1), 237\u2013256.","journal-title":"Mechanical Systems and Signal Processing"},{"issue":"1","key":"1125_CR33","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1007\/s11263-005-4939-z","volume":"70","author":"KQ Weinberger","year":"2006","unstructured":"Weinberger, K. Q., & Saul, L. K. (2006). Unsupervised learning of image manifolds by semidefinite programming. International Journal of Computer Vision, 70(1), 77\u201390.","journal-title":"International Journal of Computer Vision"},{"issue":"6","key":"1125_CR34","doi-asserted-by":"crossref","first-page":"1267","DOI":"10.1007\/s10845-012-0665-2","volume":"24","author":"LJ Wells","year":"2013","unstructured":"Wells, L. J., Megahed, F. M., Niziolek, C. B., Camelio, J. A., & Woodall, W. H. (2013). Statistical process monitoring approach for high-density point clouds. Journal of Intelligent Manufacturing, 24(6), 1267\u20131279.","journal-title":"Journal of Intelligent Manufacturing"},{"key":"1125_CR35","doi-asserted-by":"crossref","unstructured":"Yan, R. Q., & Gao, R. X. (2008). Rotary machine health diagnosis based on empirical mode decomposition. Journal of Vibration and Acoustics-Transactions of the Asme, 130(2), 1\u201312.","DOI":"10.1115\/1.2827360"},{"issue":"5","key":"1125_CR36","doi-asserted-by":"crossref","first-page":"933","DOI":"10.1007\/s10845-013-0785-3","volume":"25","author":"HC Yu","year":"2014","unstructured":"Yu, H. C., Lin, K. Y., & Chien, C. F. (2014). Hierarchical indices to detect equipment condition changes with high dimensional data for semiconductor manufacturing. Journal of Intelligent Manufacturing, 25(5), 933\u2013943.","journal-title":"Journal of Intelligent Manufacturing"},{"issue":"1","key":"1125_CR37","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1137\/S1064827502419154","volume":"26","author":"ZY Zhang","year":"2004","unstructured":"Zhang, Z. Y., & Zha, H. Y. (2004). Principal manifolds and nonlinear dimensionality reduction via tangent space alignment. SIAM Journal on Scientific Computing, 26(1), 313\u2013338.","journal-title":"SIAM Journal on Scientific Computing"},{"issue":"6","key":"1125_CR38","doi-asserted-by":"crossref","first-page":"1213","DOI":"10.1007\/s10845-012-0657-2","volume":"24","author":"ZY Zhang","year":"2013","unstructured":"Zhang, Z. Y., Wang, Y., & Wang, K. S. (2013). Fault diagnosis and prognosis using wavelet packet decomposition, fourier transform and artificial neural network. Journal of Intelligent Manufacturing, 24(6), 1213\u20131227.","journal-title":"Journal of Intelligent Manufacturing"}],"container-title":["Journal of Intelligent Manufacturing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10845-015-1125-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10845-015-1125-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10845-015-1125-6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10845-015-1125-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,30]],"date-time":"2019-05-30T22:18:55Z","timestamp":1559254735000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10845-015-1125-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,7,10]]},"references-count":38,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2018,2]]}},"alternative-id":["1125"],"URL":"https:\/\/doi.org\/10.1007\/s10845-015-1125-6","relation":{},"ISSN":["0956-5515","1572-8145"],"issn-type":[{"value":"0956-5515","type":"print"},{"value":"1572-8145","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,7,10]]}}}