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  2. Fault detection and isolation - Wikipedia

    en.wikipedia.org/wiki/Fault_detection_and_isolation

    Fault detection, isolation, and recovery (FDIR) is a subfield of control engineering which concerns itself with monitoring a system, identifying when a fault has occurred, and pinpointing the type of fault and its location. Two approaches can be distinguished: A direct pattern recognition of sensor readings that indicate a fault and an analysis ...

  3. Predictive maintenance - Wikipedia

    en.wikipedia.org/wiki/Predictive_maintenance

    Machine Learning approaches are adopted for the forecasting of its future states. [3] Some of the main components that are necessary for implementing predictive maintenance are data collection and preprocessing, early fault detection, fault detection, time to failure prediction, and maintenance scheduling and resource optimization. [4]

  4. Prognostics - Wikipedia

    en.wikipedia.org/wiki/Prognostics

    Data-driven prognostics usually use pattern recognition and machine learning techniques to detect changes in system states. [3] The classical data-driven methods for nonlinear system prediction include the use of stochastic models such as the autoregressive (AR) model, the threshold AR model, the bilinear model, the projection pursuit, the multivariate adaptive regression splines, and the ...

  5. Anomaly detection - Wikipedia

    en.wikipedia.org/wiki/Anomaly_detection

    Supervised anomaly detection techniques require a data set that has been labeled as "normal" and "abnormal" and involves training a classifier. However, this approach is rarely used in anomaly detection due to the general unavailability of labelled data and the inherent unbalanced nature of the classes.

  6. Failure mode, effects, and criticality analysis - Wikipedia

    en.wikipedia.org/wiki/Failure_Mode,_Effects,_and...

    Before detailed analysis takes place, ground rules and assumptions are usually defined and agreed to. This might include, for example: Standardized mission profile with specific fixed duration mission phases; Sources for failure rate and failure mode data; Fault detection coverage that system built-in test will realize

  7. Failure analysis - Wikipedia

    en.wikipedia.org/wiki/Failure_analysis

    Failure analysis is the process of collecting and analyzing data to determine the cause of a failure, often with the goal of determining corrective actions or liability.. According to Bloch and Geitner, ”machinery failures reveal a reaction chain of cause and effect… usually a deficiency commonly referred to as the symptom…”

  8. Failure reporting, analysis, and corrective action system

    en.wikipedia.org/wiki/Failure_reporting...

    Failure Reporting (FR). The failures and the faults related to a system, a piece of equipment, a piece of software or a process are formally reported through a standard form (Defect Report, Failure Report). Analysis (A). Perform analysis in order to identify the root cause of failure. Corrective Actions (CA).

  9. Fault injection - Wikipedia

    en.wikipedia.org/wiki/Fault_injection

    The hardware fault injection method consists in real electrical signals injection into the DUT (devices under testing) in order to disturb it, supposedly well working, at hardware low level, and deceive the control - detection chain (if present) in order to see how and if the fault management strategy is implemented.