2020
DOI: 10.1155/2020/4516132
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Vibration Tendency Prediction Approach for Hydropower Generator Fused with Multiscale Dominant Ingredient Chaotic Analysis, Adaptive Mutation Grey Wolf Optimizer, and KELM

Abstract: Accurate vibrational tendency forecasting of hydropower generator unit (HGU) is of great significance to guarantee the safe and economic operation of hydropower station. For this purpose, a novel hybrid approach combined with multiscale dominant ingredient chaotic analysis, kernel extreme learning machine (KELM), and adaptive mutation grey wolf optimizer (AMGWO) is proposed. Among the methods, variational mode decomposition (VMD), phase space reconstruction (PSR), and singular spectrum analysis (SSA) are suita… Show more

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Cited by 22 publications
(10 citation statements)
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“…Different from the mentioned methods, VMD is a novel adaptive signal decomposition method by constructing and solving a constrained variational problem to achieve signal decomposition, thus avoiding the mode mixing in EMD, the noise effect in EEMD and the basis function selection in WT. Additionally, the ability and effectiveness of VMD in signal decomposition have been demonstrated in previous literature [14]- [16]. Therefore, VMD is adopted to preprocess the non-stationary vibration signals in this paper.…”
Section: Introductionmentioning
confidence: 80%
“…Different from the mentioned methods, VMD is a novel adaptive signal decomposition method by constructing and solving a constrained variational problem to achieve signal decomposition, thus avoiding the mode mixing in EMD, the noise effect in EEMD and the basis function selection in WT. Additionally, the ability and effectiveness of VMD in signal decomposition have been demonstrated in previous literature [14]- [16]. Therefore, VMD is adopted to preprocess the non-stationary vibration signals in this paper.…”
Section: Introductionmentioning
confidence: 80%
“…Additionally, the complex structure of HGU is displayed in Figure 5. 37 Due to the complexity of the actual operating environment of HGU, it is difficult to ensure that the measured vibration signals have a uniform time interval. Based on this, the measured vibration signals that meet the average time interval are selected for experimentally analyzing to meet the actual needs of the project in this study.…”
Section: Engineering Applicationmentioning
confidence: 99%
“…The optimization parameters of the involved models are shown in Table 2, and σ represents the standard deviation value of the sequence obtained by CEEMDAN. The grid search algorithm is used to select the internal parameters of SVR in the comparison model [37], and the search range is [2 −10 , 2 10 ]. Other important parameters are set by trial and error and predetermined parameter values, as detailed in Table 2.…”
Section: B Engineering Applicationmentioning
confidence: 99%