Method for solving the problem of adequacy optimization of energy power systems based on simulated annealing

Boyarkin, Denis; Krupenev, Dmitry; Iakubovskii, Dmitrii

doi:10.1109/isse51541.2021.9582532

Cited by 1 publication

(1 citation statement)

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“…Common multi-sensor information fusion technologies include the logic filter method [6] , the simulated annealing method [7] , etc. Although these methods contain a lot of fault information during the fusion, the recognition accuracy is poor, and the information sensitivity of different positions of the meta-action unit is different, so it is necessary to consider the influence of the correlation degree of each piece of information on the recognition.…”

Section: Introductionmentioning

confidence: 99%

Meta-action unit fault identification based on multisource information fusion and D-S evidence theory

Ge,

luo

2024

Ninth International Symposium on Sensors, Mechatronics, and Automation System (ISSMAS 2023)

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Aiming at the problem of limited fault information of a single sensor and low fault identification rate in the meta-action unit's fault identification process, a meta-action unit's fault identification method based on multi-source information fusion and D-S evidence is proposed. Firstly, the fault identification framework of the mechanical element action unit is established, and multi-source information acquisition and pre-processing are carried out on the built signal acquisition test platform of the mechanical element action unit; Then, the grey correlation method is used to analyze the correlation degree of the multi-source information of the meta-action unit, and the multi-source information fusion of the metaaction unit is realized based on the covariance cross method; Finally, the D-S evidence theory is used to complete the fault identification of the meta-action unit. This method is applied to the fault identification of the ball screw element action unit and compared with the single vibration signal and the traditional information fusion method to verify the accuracy and superiority of this method.

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Section: Introductionmentioning

confidence: 99%