Feature extraction is an important part of signal processing,which is significant for signal detection,classification,and recognition.The nonlinear dynamic analysis method can extract the nonlinear characteristics of ...Feature extraction is an important part of signal processing,which is significant for signal detection,classification,and recognition.The nonlinear dynamic analysis method can extract the nonlinear characteristics of signals and is widely used in different fields.Reverse dispersion entropy(RDE)proposed by us recently,as a nonlinear dynamic analysis method,has the advantages of fast computing speed and strong anti-noise ability,which is more suitable for measuring the complexity of signal than traditional permutation entropy(PE)and dispersion entropy(DE).Empirical wavelet transform(EWT),based on the theory of wavelet analysis,can decompose a complex non-stationary signal into a number of empirical wavelet functions(EWFs)with compact support set spectrum,which has better decomposition performance than empirical mode decomposition(EMD)and its improved algorithms.Considering the advantages of RDE and EWT,on the one hand,we introduce EWT into the field of underwater acoustic signal processing and fault diagnosis to improve the signal decomposition accuracy;on the other hand,we use RDE as the features of EWFs to improve the signal separability and stability.Finally,we propose a novel signal feature extraction technology based on EWT and RDE in this paper.Experimental results show that the proposed feature extraction technology can effectively extract the complexity features of actual signals.Moreover,it also has higher distinguishing ability for different types of signals than five latest feature extraction technologies.展开更多
在燃气聚乙烯(PE)管道风险评价过程中,为降低风险因素的模糊性、不确定性对评价准确性的影响,在模糊推理的基础上,提出一种基于模糊Petri网(Fuzzy Petri net,FPN)的燃气PE管道风险评价方法。首先对燃气PE管道主要风险因素进行分析,以燃...在燃气聚乙烯(PE)管道风险评价过程中,为降低风险因素的模糊性、不确定性对评价准确性的影响,在模糊推理的基础上,提出一种基于模糊Petri网(Fuzzy Petri net,FPN)的燃气PE管道风险评价方法。首先对燃气PE管道主要风险因素进行分析,以燃气PE管道事故为顶事件,建立一个包括3个二级指标和16个三级指标的层次化评价指标体系;然后将风险评价指标体系转换为FPN模型,并运用层次分析法(AHP)和熵权法组合求取各评价指标的权重值,既避免了主观赋权的主观性和盲目性,又避免了客观赋权的片面性和机械性;最后根据模糊Petri网模型给出模糊推理算法,并应用模糊推理算法进行燃气PE管道风险评价。实例分析表明:与传统的风险评价方法相比,应用模糊Petri网的燃气PE管道风险评价方法得出的结果更加客观和准确。展开更多
基金the supported by National Natural Science Foundation of China(No.61871318 and 11574250)Scientific Research Plan Projects of Shaanxi Education Department(No.19JK0568).
文摘Feature extraction is an important part of signal processing,which is significant for signal detection,classification,and recognition.The nonlinear dynamic analysis method can extract the nonlinear characteristics of signals and is widely used in different fields.Reverse dispersion entropy(RDE)proposed by us recently,as a nonlinear dynamic analysis method,has the advantages of fast computing speed and strong anti-noise ability,which is more suitable for measuring the complexity of signal than traditional permutation entropy(PE)and dispersion entropy(DE).Empirical wavelet transform(EWT),based on the theory of wavelet analysis,can decompose a complex non-stationary signal into a number of empirical wavelet functions(EWFs)with compact support set spectrum,which has better decomposition performance than empirical mode decomposition(EMD)and its improved algorithms.Considering the advantages of RDE and EWT,on the one hand,we introduce EWT into the field of underwater acoustic signal processing and fault diagnosis to improve the signal decomposition accuracy;on the other hand,we use RDE as the features of EWFs to improve the signal separability and stability.Finally,we propose a novel signal feature extraction technology based on EWT and RDE in this paper.Experimental results show that the proposed feature extraction technology can effectively extract the complexity features of actual signals.Moreover,it also has higher distinguishing ability for different types of signals than five latest feature extraction technologies.
文摘在燃气聚乙烯(PE)管道风险评价过程中,为降低风险因素的模糊性、不确定性对评价准确性的影响,在模糊推理的基础上,提出一种基于模糊Petri网(Fuzzy Petri net,FPN)的燃气PE管道风险评价方法。首先对燃气PE管道主要风险因素进行分析,以燃气PE管道事故为顶事件,建立一个包括3个二级指标和16个三级指标的层次化评价指标体系;然后将风险评价指标体系转换为FPN模型,并运用层次分析法(AHP)和熵权法组合求取各评价指标的权重值,既避免了主观赋权的主观性和盲目性,又避免了客观赋权的片面性和机械性;最后根据模糊Petri网模型给出模糊推理算法,并应用模糊推理算法进行燃气PE管道风险评价。实例分析表明:与传统的风险评价方法相比,应用模糊Petri网的燃气PE管道风险评价方法得出的结果更加客观和准确。
