Study on Performance Parameters of Short-Secondary Type Slotless Permanent Magnet Linear Synchronous Motor Based on Analytic Method

Hao, Lei; Yin, Xiaoju

doi:10.1007/s42835-021-00865-8

Cited by 1 publication

(1 citation statement)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Fault diagnosis is a means of identifying fault modes through various methods [1][2][3][4], and has become an important approach to ensure the stable operation of mechanical machinery. Previous fault diagnosis methods typically relied on a single information source to diagnose machinery [5,6].…”

Section: Introductionmentioning

confidence: 99%

Fault diagnosis method for machinery based on multi-source conflict information fusion

Wei¹,

Zhang²,

Lu³

et al. 2022

Meas. Sci. Technol.

View full text Add to dashboard Cite

Multi-source information fusion diagnosis is usually more reliable than the fault diagnosis with single-source employed. However, fusion resultsmaybe absurdity while fusing the highly conflicting information. To address this problem, the DS evidence theory is updated by weighting each evidence according to the corresponding contribution to the decision and a novel fault diagnosis method based on multi-source conflict information fusion is proposed. First, the basic probability assignment of evidence corresponding to the sensor information is given by introducing the feature parameters of electromyographic signals and using the BP neural network. Then, the importance of each evidence is determined by solving the difference degree and exclusion degree among the evidence, and the evidences are assigned weights according to the importance degree of each evidence in the fusion decision-making process. Next, weighted evidence are combined for making decision and further diagnosis after weighted averaging the evidences with different weights. In the end, the performance of the proposed method is assessed by the receiver operating characteristic (ROC). The experimental results show that the area under the ROC curves the proposed method are 0.3229, 0.0729, and 0.9271, higher than those of the traditional DS’s method, Murphy’s method, and Yager’s method, respectively, which proves that the proposed method has better diagnostic performance and reliability.

show abstract