H
Hong Qing
Researcher at University of Shanghai for Science and Technology
Publications - 3
Citations - 151
Hong Qing is an academic researcher from University of Shanghai for Science and Technology. The author has contributed to research in topics: Fault (power engineering) & Fault detection and isolation. The author has an hindex of 3, co-authored 3 publications receiving 88 citations.
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Least squares support vector machine (LS-SVM)-based chiller fault diagnosis using fault indicative features
TL;DR: The results indicated that as compared with the other two machine learning methods, the proposed LS-SVM model with optimization showed a better FDD performance in terms of the overall correct rate for all the samples, the individual correct rates for each fault, the diagnostic efficiency, the detection rate and the false alarm rate, etc.
Journal ArticleDOI
Comparative study of probabilistic neural network and back propagation network for fault diagnosis of refrigeration systems
TL;DR: The overall diagnostic performance of the probabilistic neural network was better than that of the back-propagation network and it was demonstrated that system-level faults were more difficult to be recognized by the model than component- level faults because of their widespread influence on the system operation.
Journal ArticleDOI
Application of PSO-LSSVM and hybrid programming to fault diagnosis of refrigeration systems
TL;DR: A novel hybrid model by introducing particle swarm optimization into least squares support vector machine (LSSVM) for parameter optimization to overcome the blindness of parameter selection is presented, and a novel idea of hybrid programming is proposed, where MATLAB is used to implement the FDD strategy and LabVIEW is employed for interface creation to take the advantage of both sides.