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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 ...
Here are some methods that can aid fault injection to efficiently explore the fault space to reach higher fault coverage in less simulation time. Sensitivity analysis: [ 9 ] In this method, sensitivity analysis has been used to identify the most important signals that have a higher impact on the system's specification.
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.
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…”
ATPG (acronym for both automatic test pattern generation and automatic test pattern generator) is an electronic design automation method or technology used to find an input (or test) sequence that, when applied to a digital circuit, enables automatic test equipment to distinguish between the correct circuit behavior and the faulty circuit behavior caused by defects.
graph with an example of steps in a failure mode and effects analysis. Failure mode and effects analysis (FMEA; often written with "failure modes" in plural) is the process of reviewing as many components, assemblies, and subsystems as possible to identify potential failure modes in a system and their causes and effects.
Isolation Forest is an algorithm for data anomaly detection using binary trees.It was developed by Fei Tony Liu in 2008. [1] It has a linear time complexity and a low memory use, which works well for high-volume data.
CHAID is based on a formal extension of AID (Automatic Interaction Detection) [4] and THAID (THeta Automatic Interaction Detection) [5] [6] procedures of the 1960s and 1970s, which in turn were extensions of earlier research, including that performed by Belson in the UK in the 1950s. [7] In 1975, the CHAID technique itself was developed in ...