Early Fault Estimation of Inter-turn Short-circuit in Rotor Winding of WRIM using ANN-based Combined TSA and MCSA Technique

Sabir, Hamza; Ouassaid, Mohammed; Ngote, Nabil

doi:10.1109/isaect50560.2020.9523697

Cited by 2 publications

(1 citation statement)

References 19 publications

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“…Regarding the analysis of current signals, Motor Current Signature Analysis (MCSA) is a common practice to diagnose different rotating machinery, as is the case of induction machines [103], permanent magnet synchronous motors [104], or rolling element bearings [105]. This strategy is also complemented with other signal processing techniques such as adaptive filters such as the Wiener filter [106] or time-synchronous averaging [107].…”

Section: Data Preprocessingmentioning

confidence: 99%

A Review of Multisensor Data Fusion Solutions in Smart Manufacturing: Systems and Trends

Tsanousa

Bektsis

Kyriakopoulos

et al. 2022

Sensors

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Manufacturing companies increasingly become “smarter” as a result of the Industry 4.0 revolution. Multiple sensors are used for industrial monitoring of machines and workers in order to detect events and consequently improve the manufacturing processes, lower the respective costs, and increase safety. Multisensor systems produce big amounts of heterogeneous data. Data fusion techniques address the issue of multimodality by combining data from different sources and improving the results of monitoring systems. The current paper presents a detailed review of state-of-the-art data fusion solutions, on data storage and indexing from various types of sensors, feature engineering, and multimodal data integration. The review aims to serve as a guide for the early stages of an analytic pipeline of manufacturing prognosis. The reviewed literature showed that in fusion and in preprocessing, the methods chosen to be applied in this sector are beyond the state-of-the-art. Existing weaknesses and gaps that lead to future research goals were also identified.

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