Forecasting Models for Hydropower Unit Stability Using LS-SVM. (28th May 2015)

• Record Type: Journal Article
• Authors: Qiao, Liangliang; Chen, Qijuan
• Other Names: Small Michael Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2015(2015)
• Publication Date: 2015-05-28
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2015/350148
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : This paper discusses a least square support vector machine (LS-SVM) approach for forecasting stability parameters of Francis turbine unit. To achieve training and testing data for the models, four field tests were presented, especially for the vibration inY -direction of lower generator bearing (LGB) and pressure in draft tube (DT). A heuristic method such as a neural network using Backpropagation (NNBP) is introduced as a comparison model to examine the feasibility of forecasting performance. In the experimental results, LS-SVM showed superior forecasting accuracies and performances to the NNBP, which is of significant importance to better monitor the unit safety and potential faults diagnosis.