Huang Jinying

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PCB fault detection and positioning is always a complex and difficult work. This thesis designed a fault diagnosis system for PCB circuit, which uses voltage signals as incentive signals and the voltage or current response signals as the output. Fault tree is established and fault searching and positioning method introduced fault dictionary analysis(More)
For blindness of the parameter settings in kernel principal component analysis (KPCA), kernel function parameter optimized by particle swarm optimization algorithm (PSO) is proposed, and KPCA is applied to feature extraction. The mathematical model of kernel function parameter optimized is constructed firstly, then the particle swarm optimization algorithm(More)
In this paper, SOBI blind source separation algorithm is applying to extract the fault feature of gearbox vibration signal. It is Tested and verified by BP neural network for fault diagnosis. The result shows that the fault feature extraction method based on blind source separation for gearbox fault diagnosis is very effective.
In the fault diagnosis of gearbox, the extraction of the fault signal is a key problem. The practical testing vibration signal of gearbox is no stable or Gauss distributing. In different fault states, the vibration signal has different Gauss property and symmetry property, usually including stronger noise and low SNR. Faint fault information is often(More)
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