On-Site Calibration of an Electric Drive: A Case Study Using a Multiphase System

Soto-Marchena, David; Barrero, Federico; Colodro, Francisco; Arahal, Manuel R.; Mora, Jose L.

doi:10.3390/s23177317

Cited by 2 publications

(1 citation statement)

References 22 publications

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“…An on-site sensor calibration method was proposed for the quality assurance of process separation measurements, which can guarantee the optimal performance of the sensor measuring system and assure a high measurement quality between company inspections [4]. More reviews can be found in [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Electrical Sensor Calibration by Fuzzy Clustering with Mandatory Constraint

Yue,

Fu,

Liu

et al. 2024

Sensors

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Electrical tomography sensors have been widely used for pipeline parameter detection and estimation. Before they can be used in formal applications, the sensors must be calibrated using enough labeled data. However, due to the high complexity of actual measuring environments, the calibrated sensors are inaccurate since the labeling data may be uncertain, inconsistent, incomplete, or even invalid. Alternatively, it is always possible to obtain partial data with accurate labels, which can form mandatory constraints to correct errors in other labeling data. In this paper, a semi-supervised fuzzy clustering algorithm is proposed, and the fuzzy membership degree in the algorithm leads to a set of mandatory constraints to correct these inaccurate labels. Experiments in a dredger validate the proposed algorithm in terms of its accuracy and stability. This new fuzzy clustering algorithm can generally decrease the error of labeling data in any sensor calibration process.

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