Nowadays,the internal structure of spacecraft has been increasingly complex.As its“lifeline”,cables require extensive manpower and resources for manual testing,and it is challenging to quickly and accurately locate ...Nowadays,the internal structure of spacecraft has been increasingly complex.As its“lifeline”,cables require extensive manpower and resources for manual testing,and it is challenging to quickly and accurately locate quality problems and find solutions.To address this problem,a knowledge graph based method is employed to extract multi-source heterogeneous cable knowledge entities.The method utilizes the bidirectional encoder representations from transformers(BERT)network to embed word vectors into the input text,then extracts the contextual features of the input sequence through the bidirectional long short-term memory(BiLSTM)network,and finally inputs them into the conditional random field(CRF)network to predict entity categories.Simultaneously,by using the entities extracted by this model as the data layer,a knowledge graph based method has been constructed.Compared to other traditional extraction methods,the entity extraction method used in this study demonstrates significant improvements in metrics such as precision,recall and an F1 score.Ultimately,employing cable test data from a particular aerospace precision machining company,the study has constructed the knowledge graph based method in the field to achieve visualized queries and the traceability and localization of quality problems.展开更多
To solve the problem of mismatching features in an experimental database, which is a key technique in the field of cross-corpus speech emotion recognition, an auditory attention model based on Chirplet is proposed for...To solve the problem of mismatching features in an experimental database, which is a key technique in the field of cross-corpus speech emotion recognition, an auditory attention model based on Chirplet is proposed for feature extraction.First, in order to extract the spectra features, the auditory attention model is employed for variational emotion features detection. Then, the selective attention mechanism model is proposed to extract the salient gist features which showtheir relation to the expected performance in cross-corpus testing.Furthermore, the Chirplet time-frequency atoms are introduced to the model. By forming a complete atom database, the Chirplet can improve the spectrum feature extraction including the amount of information. Samples from multiple databases have the characteristics of multiple components. Hereby, the Chirplet expands the scale of the feature vector in the timefrequency domain. Experimental results show that, compared to the traditional feature model, the proposed feature extraction approach with the prototypical classifier has significant improvement in cross-corpus speech recognition. In addition, the proposed method has better robustness to the inconsistent sources of the training set and the testing set.展开更多
为了分析和评估500 k V交联聚乙烯(XLPE)电力电缆线路的绝缘状况并开展电缆绝缘诊断,基于超高压电力电缆的局部放电机理和局部放电信号衰减特性,首次提出了应用分布式局部放电监测技术进行500 k V电力电缆在线监测的新模式。实践中发现...为了分析和评估500 k V交联聚乙烯(XLPE)电力电缆线路的绝缘状况并开展电缆绝缘诊断,基于超高压电力电缆的局部放电机理和局部放电信号衰减特性,首次提出了应用分布式局部放电监测技术进行500 k V电力电缆在线监测的新模式。实践中发现有3种现场局部放电提取信号方式可以满足500 k V电力电缆在线监测的实际需要。通过采用分布式时频分析技术,有效地解决了500 k V电力电缆绝缘缺陷的识别问题,提高了绝缘缺陷定位的精度。应用局部放电图谱库大数据分析技术及3图谱局部放电识别法,首次成功实现了500 k V电力电缆的绝缘诊断。开发了局部放电信号智能式进阶报警策略,提高了局部放电报警的可靠性。研究成果在国内首条长距离敷设的500 k V交联聚乙烯(XLPE)电力电缆线路上得到了成功应用。研究认为综合应用分布式时频分析、3图谱局部放电识别法和智能式进阶报警策略等分布式局部放电在线监测新技术,可以实现500 k V电力电缆绝缘缺陷的识别、定位和诊断;将对国内后续500 k V电力电缆开展局部放电监测和缺陷识别具有积极的指导意义。展开更多
Successful restoration of blurred images depends primarily on the knowledge about the degradationparameter.Defocus blur model in the frequency domain is characterized by concentric rings and the blurradius of the poin...Successful restoration of blurred images depends primarily on the knowledge about the degradationparameter.Defocus blur model in the frequency domain is characterized by concentric rings and the blurradius of the point spread function(PSF)can be identified conveniently in the frequency field for peopleby manual means rather than for computer.This paper introduces a practical method for computer to esti-mate the defocus blur parameter in cepstrum area.Fourier transform plays an intermediate role in the pathto cepstrum domain.We suggest a weighted adjustment operation in the frequency domain and then con-vert it to the cepstrum field to increase the accuracy of recognition.展开更多
A new identity-based （ID-based） aggregate signature scheme which does not need any kind of interaction among the signers was proposed to provide partial aggregation. Compared with the existing ID-based aggregate sig...A new identity-based （ID-based） aggregate signature scheme which does not need any kind of interaction among the signers was proposed to provide partial aggregation. Compared with the existing ID-based aggregate signatures, the scheme is more efficient in terms of computational cost, Security in the random oracle model based on a variant of the computation Diflle-Hellman （CDH） problem is captured.展开更多
文摘Nowadays,the internal structure of spacecraft has been increasingly complex.As its“lifeline”,cables require extensive manpower and resources for manual testing,and it is challenging to quickly and accurately locate quality problems and find solutions.To address this problem,a knowledge graph based method is employed to extract multi-source heterogeneous cable knowledge entities.The method utilizes the bidirectional encoder representations from transformers(BERT)network to embed word vectors into the input text,then extracts the contextual features of the input sequence through the bidirectional long short-term memory(BiLSTM)network,and finally inputs them into the conditional random field(CRF)network to predict entity categories.Simultaneously,by using the entities extracted by this model as the data layer,a knowledge graph based method has been constructed.Compared to other traditional extraction methods,the entity extraction method used in this study demonstrates significant improvements in metrics such as precision,recall and an F1 score.Ultimately,employing cable test data from a particular aerospace precision machining company,the study has constructed the knowledge graph based method in the field to achieve visualized queries and the traceability and localization of quality problems.
基金The National Natural Science Foundation of China(No.61273266,61231002,61301219,61375028)the Specialized Research Fund for the Doctoral Program of Higher Education(No.20110092130004)the Natural Science Foundation of Shandong Province(No.ZR2014FQ016)
文摘To solve the problem of mismatching features in an experimental database, which is a key technique in the field of cross-corpus speech emotion recognition, an auditory attention model based on Chirplet is proposed for feature extraction.First, in order to extract the spectra features, the auditory attention model is employed for variational emotion features detection. Then, the selective attention mechanism model is proposed to extract the salient gist features which showtheir relation to the expected performance in cross-corpus testing.Furthermore, the Chirplet time-frequency atoms are introduced to the model. By forming a complete atom database, the Chirplet can improve the spectrum feature extraction including the amount of information. Samples from multiple databases have the characteristics of multiple components. Hereby, the Chirplet expands the scale of the feature vector in the timefrequency domain. Experimental results show that, compared to the traditional feature model, the proposed feature extraction approach with the prototypical classifier has significant improvement in cross-corpus speech recognition. In addition, the proposed method has better robustness to the inconsistent sources of the training set and the testing set.
文摘为了分析和评估500 k V交联聚乙烯(XLPE)电力电缆线路的绝缘状况并开展电缆绝缘诊断,基于超高压电力电缆的局部放电机理和局部放电信号衰减特性,首次提出了应用分布式局部放电监测技术进行500 k V电力电缆在线监测的新模式。实践中发现有3种现场局部放电提取信号方式可以满足500 k V电力电缆在线监测的实际需要。通过采用分布式时频分析技术,有效地解决了500 k V电力电缆绝缘缺陷的识别问题,提高了绝缘缺陷定位的精度。应用局部放电图谱库大数据分析技术及3图谱局部放电识别法,首次成功实现了500 k V电力电缆的绝缘诊断。开发了局部放电信号智能式进阶报警策略,提高了局部放电报警的可靠性。研究成果在国内首条长距离敷设的500 k V交联聚乙烯(XLPE)电力电缆线路上得到了成功应用。研究认为综合应用分布式时频分析、3图谱局部放电识别法和智能式进阶报警策略等分布式局部放电在线监测新技术,可以实现500 k V电力电缆绝缘缺陷的识别、定位和诊断;将对国内后续500 k V电力电缆开展局部放电监测和缺陷识别具有积极的指导意义。
基金the National Natural Science Foundation of China(No.30570485)
文摘Successful restoration of blurred images depends primarily on the knowledge about the degradationparameter.Defocus blur model in the frequency domain is characterized by concentric rings and the blurradius of the point spread function(PSF)can be identified conveniently in the frequency field for peopleby manual means rather than for computer.This paper introduces a practical method for computer to esti-mate the defocus blur parameter in cepstrum area.Fourier transform plays an intermediate role in the pathto cepstrum domain.We suggest a weighted adjustment operation in the frequency domain and then con-vert it to the cepstrum field to increase the accuracy of recognition.
文摘A new identity-based （ID-based） aggregate signature scheme which does not need any kind of interaction among the signers was proposed to provide partial aggregation. Compared with the existing ID-based aggregate signatures, the scheme is more efficient in terms of computational cost, Security in the random oracle model based on a variant of the computation Diflle-Hellman （CDH） problem is captured.
