Download Data-Driven Technology for Engineering Systems Health by Gang Niu PDF

By Gang Niu

This booklet introduces condition-based upkeep (CBM)/data-driven prognostics and wellbeing and fitness administration (PHM) intimately, first explaining the PHM layout method from a platforms engineering point of view, then summarizing and elaborating at the data-driven method for function development, in addition to feature-based fault analysis and analysis. The ebook incorporates a wealth of illustrations and tables to aid clarify the algorithms, in addition to useful examples exhibiting how one can use this software to resolve occasions for which analytic ideas are poorly appropriate. It equips readers to use the options mentioned that allows you to research and clear up various difficulties in PHM method layout, function building, fault analysis and prognosis.

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Extra resources for Data-Driven Technology for Engineering Systems Health Management: Design Approach, Feature Construction, Fault Diagnosis, Prognosis, Fusion and Decisions

Example text

2. Residual signal is a signal that represents a deviation from standard operating conditions which is generated by comparing, for example, a model output with the actual system output. Based on this signal, one makes decision about the operating condition of the machinery. The other techniques for fault detection are model-based and data-driven, as shown in Fig. 3. Model-based technique relies on an accurate dynamic model of the system and is capable for detecting even unanticipated faults. It takes advantage of the actual system and model outputs to generate a discrepancy or residual, as it is known, between two outputs that are indicative of a potential fault condition.

Yam et al. 2001). Failure analysis is the process of collecting and analyzing data to determine the cause of a failure and how to prevent it from recurring. It is an important discipline in many branches of manufacturing industry, where it is a vital tool used in the development of new products and for the improvement of existing products. Fault diagnosis is detecting, isolating, and identifying and impending incipient failure condition, while the affected components (subsystem, system) are still operational even though at a degraded mode.

4 Role of Condition Monitoring, Fault Diagnosis, and Prognosis Data-driven PHM/CBM seeks to implement a policy wherein maintenance management decisions are based on the identification of the current condition of monitored machinery. The implementation of efficient maintenance management strategies based on CBM presupposes that adequate condition monitoring, as well as system fault diagnosis and prognosis are in place (Jardine 1973). 4 Role of Condition Monitoring, Fault Diagnosis, and Prognosis 41 known.

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