To effectively extract the interturn short circuit fault features of induction motor from stator current signal, a novel feature extraction method based on the bare-bones particle swarm optimization (BBPSO) algorith...To effectively extract the interturn short circuit fault features of induction motor from stator current signal, a novel feature extraction method based on the bare-bones particle swarm optimization (BBPSO) algorithm and wavelet packet was proposed. First, according to the maximum inner product between the current signal and the cosine basis functions, this method could precisely estimate the waveform parameters of the fundamental component using the powerful global search capability of the BBPSO, which can eliminate the fundamental component and not affect other harmonic components. Then, the harmonic components of residual current signal were decomposed to a series of frequency bands by wavelet packet to extract the interturn circuit fault features of the induction motor. Finally, the results of simulation and laboratory tests demonstrated the effectiveness of the proposed method.展开更多
To improve motion graph based motion synthesis,semantic control was introduced.Hybrid motion features including both numerical and user-defined semantic relational features were extracted to encode the characteristic ...To improve motion graph based motion synthesis,semantic control was introduced.Hybrid motion features including both numerical and user-defined semantic relational features were extracted to encode the characteristic aspects contained in the character's poses of the given motion sequences.Motion templates were then automatically derived from the training motions for capturing the spatio-temporal characteristics of an entire given class of semantically related motions.The data streams of motion documents were automatically annotated with semantic motion class labels by matching their respective motion class templates.Finally,the semantic control was introduced into motion graph based human motion synthesis.Experiments of motion synthesis demonstrate the effectiveness of the approach which enables users higher level of semantically intuitive control and high quality in human motion synthesis from motion capture database.展开更多
文摘To effectively extract the interturn short circuit fault features of induction motor from stator current signal, a novel feature extraction method based on the bare-bones particle swarm optimization (BBPSO) algorithm and wavelet packet was proposed. First, according to the maximum inner product between the current signal and the cosine basis functions, this method could precisely estimate the waveform parameters of the fundamental component using the powerful global search capability of the BBPSO, which can eliminate the fundamental component and not affect other harmonic components. Then, the harmonic components of residual current signal were decomposed to a series of frequency bands by wavelet packet to extract the interturn circuit fault features of the induction motor. Finally, the results of simulation and laboratory tests demonstrated the effectiveness of the proposed method.
基金Project(60801053) supported by the National Natural Science Foundation of ChinaProject(4082025) supported by the Beijing Natural Science Foundation,China+4 种基金Project(20070004037) supported by the Doctoral Foundation of ChinaProject(2009JBM135,2011JBM023) supported by the Fundamental Research Funds for the Central Universities of ChinaProject(151139522) supported by the Hongguoyuan Innovative Talent Program of Beijing Jiaotong University,ChinaProject(YB20081000401) supported by the Beijing Excellent Doctoral Thesis Program,ChinaProject (2006CB303105) supported by the National Basic Research Program of China
文摘To improve motion graph based motion synthesis,semantic control was introduced.Hybrid motion features including both numerical and user-defined semantic relational features were extracted to encode the characteristic aspects contained in the character's poses of the given motion sequences.Motion templates were then automatically derived from the training motions for capturing the spatio-temporal characteristics of an entire given class of semantically related motions.The data streams of motion documents were automatically annotated with semantic motion class labels by matching their respective motion class templates.Finally,the semantic control was introduced into motion graph based human motion synthesis.Experiments of motion synthesis demonstrate the effectiveness of the approach which enables users higher level of semantically intuitive control and high quality in human motion synthesis from motion capture database.