000 | 04272nam a22006375i 4500 | ||
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001 | 978-3-319-56126-4 | ||
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_a9783319561264 _9978-3-319-56126-4 |
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024 | 7 |
_a10.1007/978-3-319-56126-4 _2doi |
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_aStructural Health Monitoring _h[electronic resource] : _bAn Advanced Signal Processing Perspective / _cedited by Ruqiang Yan, Xuefeng Chen, Subhas Chandra Mukhopadhyay. |
250 | _a1st ed. 2017. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2017. |
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300 |
_aXI, 375 p. 284 illus., 175 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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490 | 1 |
_aSmart Sensors, Measurement and Instrumentation, _x2194-8410 ; _v26 |
|
505 | 0 | _aAdvanced Signal Processing for Structural Health Monitoring -- Signal Post-Processing for Accurate Evaluation of the Natural Frequencies -- Holobalancing Method and its Improvement by Reselection of Balancing Object -- Wavelet Transform Based On Inner Product for Fault Diagnosis of Rotating Machinery -- Wavelet Based Spectral Kurtosis and Kurtogram: A Smart and Sparse Characterization of Impulsive Transient Vibration -- Time-Frequency Manifold for Machinery Fault Diagnosis -- Matching Demodulation Transform and its Application in Machine Fault Diagnosis -- Compressive Sensing: A New Insight to Condition Monitoring of Rotary Machinery -- Sparse Representation of the Transients in Mechanical Signals -- Fault Diagnosis of Rotating Machinery Based on Empirical Mode Decomposition -- Bivariate Empirical Mode Decomposition and Its Applications in Machine Condition Monitoring -- Time-Frequency Demodulation Analysis Based on LMD and Its Applications -- On The Use of Stochastic Resonance in Mechanical Fault Signal Detection. | |
520 | _aThis book highlights the latest advances and trends in advanced signal processing (such as wavelet theory, time-frequency analysis, empirical mode decomposition, compressive sensing and sparse representation, and stochastic resonance) for structural health monitoring (SHM). Its primary focus is on the utilization of advanced signal processing techniques to help monitor the health status of critical structures and machines encountered in our daily lives: wind turbines, gas turbines, machine tools, etc. As such, it offers a key reference guide for researchers, graduate students, and industry professionals who work in the field of SHM. | ||
650 | 0 |
_aSignal processing. _94052 |
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650 | 0 |
_aBiomedical engineering. _93292 |
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650 | 0 |
_aIndustrial engineering. _931641 |
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650 | 0 |
_aProduction engineering. _93683 |
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650 | 0 |
_aMeasurement. _928731 |
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650 | 0 |
_aMeasuring instruments. _910420 |
|
650 | 1 | 4 |
_aSignal, Speech and Image Processing . _931566 |
650 | 2 | 4 |
_aBiomedical Engineering and Bioengineering. _931842 |
650 | 2 | 4 |
_aIndustrial and Production Engineering. _931644 |
650 | 2 | 4 |
_aMeasurement Science and Instrumentation. _932783 |
700 | 1 |
_aYan, Ruqiang. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _959796 |
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700 | 1 |
_aChen, Xuefeng. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _959797 |
|
700 | 1 |
_aMukhopadhyay, Subhas Chandra. _eeditor. _0(orcid)0000-0002-8600-5907 _1https://orcid.org/0000-0002-8600-5907 _4edt _4http://id.loc.gov/vocabulary/relators/edt _959798 |
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710 | 2 |
_aSpringerLink (Online service) _959799 |
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773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783319561257 |
776 | 0 | 8 |
_iPrinted edition: _z9783319561271 |
776 | 0 | 8 |
_iPrinted edition: _z9783319858326 |
830 | 0 |
_aSmart Sensors, Measurement and Instrumentation, _x2194-8410 ; _v26 _959800 |
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856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-319-56126-4 |
912 | _aZDB-2-ENG | ||
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