| 000 | 02693naaaa2200505uu 4500 | ||
|---|---|---|---|
| 003 | BUT | ||
| 005 | 20230522094655.0 | ||
| 006 | m o d | ||
| 007 | cr|mn|---annan | ||
| 008 | 20220115s2022 xx |||||o ||| eng|| d | ||
| 020 | _a9789811680441 | ||
| 040 |
_aoapen _coapen |
||
| 041 | 0 | _aeng | |
| 080 | _a004.8 | ||
| 100 | 1 |
_aWang, Jing _4auth |
|
| 245 | 1 | 0 | _aData-Driven Fault Detection and Reasoning for Industrial Monitoring |
| 260 |
_bSpringer Nature _c2022 |
||
| 300 | _a1 electronic resource (264 p.) | ||
| 490 | 1 | _aIntelligent Control and Learning Systems | |
| 506 | 0 |
_aOpen Access _2star _fUnrestricted online access |
|
| 520 | _aThis open access book assesses the potential of data-driven methods in industrial process monitoring engineering. The process modeling, fault detection, classification, isolation, and reasoning are studied in detail. These methods can be used to improve the safety and reliability of industrial processes. Fault diagnosis, including fault detection and reasoning, has attracted engineers and scientists from various fields such as control, machinery, mathematics, and automation engineering. Combining the diagnosis algorithms and application cases, this book establishes a basic framework for this topic and implements various statistical analysis methods for process monitoring. This book is intended for senior undergraduate and graduate students who are interested in fault diagnosis technology, researchers investigating automation and industrial security, professional practitioners and engineers working on engineering modeling and data processing applications. This is an open access book. | ||
| 540 |
_aCreative Commons _fby/4.0/ _2cc |
||
| 546 | _aEnglish | ||
| 650 | 0 |
_aРобототехника _2bicssc _94541 |
|
| 650 | 0 |
_aИскусственный интеллект _2bicssc _94518 |
|
| 653 | _aMultivariate causality analysis | ||
| 653 | _aProcess monitoring | ||
| 653 | _aManifold learning | ||
| 653 | _aFault diagnosis | ||
| 653 | _aData modeling | ||
| 653 | _aFault classification | ||
| 653 | _aFault reasoning | ||
| 653 | _aCausal network | ||
| 653 | _aProbabilistic graphical model | ||
| 653 | _aData-driven methods | ||
| 653 | _aIndustrial monitoring | ||
| 653 | _aOpen Access | ||
| 700 | 1 |
_aZhou, Jinglin _4auth |
|
| 700 | 1 |
_aChen, Xiaolu _4auth |
|
| 830 |
_94633 _aIntelligent Control and Learning Systems |
||
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://library.oapen.org/bitstream/20.500.12657/52452/1/978-981-16-8044-1.pdf _70 _zDownload |
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://directory.doabooks.org/handle/20.500.12854/77320 _70 _zDescription |
| 909 |
_c4 _dDarya Shvetsova |
||
| 942 |
_2udc _cEE |
||
| 999 |
_c6628 _d6628 |
||