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Titlebook: Condition Monitoring Algorithms in MATLAB?; Adam Jablonski Book 2021 The Editor(s) (if applicable) and The Author(s), under exclusive lice

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31#
發(fā)表于 2025-3-26 23:03:19 | 只看該作者
Signal Processing Algorithms,ritten in MATLAB.. Each technique is accompanied by description, exemplary figure, full code, and comments. Codes cover windowing, compensation, zero-padding, filtering, resampling, integration, envelope analysis, Time-Synchronous Averaging (TSA), and phase marker processing.
32#
發(fā)表于 2025-3-27 02:53:47 | 只看該作者
33#
發(fā)表于 2025-3-27 05:53:31 | 只看該作者
34#
發(fā)表于 2025-3-27 11:44:28 | 只看該作者
Simulating Long-Term Machine Fault Development,ure Development Function (FDF). This Chapter shows how to generate data corresponding to eight different modes (i.e. clearly separated technical condition state) of a rotary machinery. Introduced faults include shaft imbalance, gearbox degradation, and rolling-element bearing failure.
35#
發(fā)表于 2025-3-27 15:04:33 | 只看該作者
36#
發(fā)表于 2025-3-27 20:07:54 | 只看該作者
37#
發(fā)表于 2025-3-27 22:17:46 | 只看該作者
Development of Interface for Direct Data Access (DDA),monitoring system in MATLAB.. The procedure uses .NET libraries, and it is described step-by-step. A special attention is given to internal MATLAB. wrapping of such functions, which significantly simplify codes. Finally, this Chapter illustrates selected possible scenarios of DDA implementation.
38#
發(fā)表于 2025-3-28 04:02:26 | 只看該作者
39#
發(fā)表于 2025-3-28 08:22:25 | 只看該作者
40#
發(fā)表于 2025-3-28 11:42:13 | 只看該作者
Proposed Approach: Transactional Agents,assessment methods. Scalar indicators covered in this Chapter range from basic statistical indicators to conceptual advanced markers. Presented figures range from basic time or frequency-domain plots to recent, advanced 3D maps.
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