On the basis of high precision requirement for input signals in the power system protection and control system,this paper,only for the influence of power system frequency deviation on extracting fundamental harmonic,s...On the basis of high precision requirement for input signals in the power system protection and control system,this paper,only for the influence of power system frequency deviation on extracting fundamental harmonic,studies the amplitude error of Fourier algorithm,presents a method of correcting frequency deviation,and further derives the formulas of improved Fourier algorithm.The simulation results verified the effectiveness of the algorithm,it not only can greatly weaken the influence of frequency deviation,but also increase the precision of the power system protection and control.As a result the study in this paper has practical application value.展开更多
Traditional short-time fractional Fourier transform(STFrFT)has a single and fixed window function,which can not be adjusted adaptively according to the characteristics of fre-quency and frequency change rate.In order ...Traditional short-time fractional Fourier transform(STFrFT)has a single and fixed window function,which can not be adjusted adaptively according to the characteristics of fre-quency and frequency change rate.In order to overcome the shortcomings,the STFrFT method with adaptive window function is proposed.In this method,the window function of STFrFT is ad-aptively adjusted by establishing a library containing multiple window functions and taking the minimum information entropy as the criterion,so as to obtain a time-frequency distribution that better matches the desired signal.This method takes into account the time-frequency resolution characteristics of STFrFT and the excellent characteristics of adaptive adjustment to window func-tion,improves the time-frequency aggregation on the basis of eliminating cross term interference,and provides a new tool for improving the time-frequency analysis ability of complex modulated sig-nals.展开更多
The parameters of abnormal data are defined and their influence on the original data and Fourier Algorithm is studied. A formula is proposed to quantify how the abnormal data influences the amplitude calculated by Fou...The parameters of abnormal data are defined and their influence on the original data and Fourier Algorithm is studied. A formula is proposed to quantify how the abnormal data influences the amplitude calculated by Fourier Algorithm. Two simulation models are established in Matlab to study the influence of abnormal data on relay protection. The simulation results show that the abnormal data can make distance protection extend the fault’s influence and make over current protection start by error.展开更多
With the rapid evolution of artificial intelligence(AI)technologies,the medical industry is undergoing a profound transformation driven by data intelligence.As the foundational element for intelligent diagnosis,precis...With the rapid evolution of artificial intelligence(AI)technologies,the medical industry is undergoing a profound transformation driven by data intelligence.As the foundational element for intelligent diagnosis,precision prevention,and public health governance,medical data is characterized by massive volume,complex structure,diverse sources,high dimensionality,strong privacy,and high timeliness.Traditional data analysis methods are no longer sufficient to meet the comprehensive requirements of data security,intelligent processing,and decision support.Through techniques such as machine learning,deep learning,natural language processing,and multimodal fusion,AI provides robust technical support for medical data cleaning,governance,mining,and application.At the data level,intelligent algorithms enable the standardization,structuring,and interoperability of medical data,promoting information sharing across medical systems.At the model level,AI supports auxiliary diagnosis and precision treatment through image recognition,medical record analysis,and knowledge graph construction.At the system level,intelligent decision-support platforms continuously enhance the efficiency and accuracy of healthcare services.However,the widespread adoption of AI in medicine still faces challenges such as privacy protection,data security,model interpretability,and the lack of unified industry standards.Based on a systematic review of AI’s key supporting technologies in medical data processing and application,this paper focuses on the compliance challenges and adaptation strategies during industry integration and proposes an adaptation framework centered on“technological trustworthiness,data security,and industry collaboration.”The study provides theoretical and practical insights for promoting the standardized and sustainable development of AI in the healthcare industry.展开更多
文摘On the basis of high precision requirement for input signals in the power system protection and control system,this paper,only for the influence of power system frequency deviation on extracting fundamental harmonic,studies the amplitude error of Fourier algorithm,presents a method of correcting frequency deviation,and further derives the formulas of improved Fourier algorithm.The simulation results verified the effectiveness of the algorithm,it not only can greatly weaken the influence of frequency deviation,but also increase the precision of the power system protection and control.As a result the study in this paper has practical application value.
基金supported by the National Natural Science Found-ation of China(No.61571454)Special Fund for Taishan Scholar Project(No.201712072)。
文摘Traditional short-time fractional Fourier transform(STFrFT)has a single and fixed window function,which can not be adjusted adaptively according to the characteristics of fre-quency and frequency change rate.In order to overcome the shortcomings,the STFrFT method with adaptive window function is proposed.In this method,the window function of STFrFT is ad-aptively adjusted by establishing a library containing multiple window functions and taking the minimum information entropy as the criterion,so as to obtain a time-frequency distribution that better matches the desired signal.This method takes into account the time-frequency resolution characteristics of STFrFT and the excellent characteristics of adaptive adjustment to window func-tion,improves the time-frequency aggregation on the basis of eliminating cross term interference,and provides a new tool for improving the time-frequency analysis ability of complex modulated sig-nals.
文摘The parameters of abnormal data are defined and their influence on the original data and Fourier Algorithm is studied. A formula is proposed to quantify how the abnormal data influences the amplitude calculated by Fourier Algorithm. Two simulation models are established in Matlab to study the influence of abnormal data on relay protection. The simulation results show that the abnormal data can make distance protection extend the fault’s influence and make over current protection start by error.
文摘With the rapid evolution of artificial intelligence(AI)technologies,the medical industry is undergoing a profound transformation driven by data intelligence.As the foundational element for intelligent diagnosis,precision prevention,and public health governance,medical data is characterized by massive volume,complex structure,diverse sources,high dimensionality,strong privacy,and high timeliness.Traditional data analysis methods are no longer sufficient to meet the comprehensive requirements of data security,intelligent processing,and decision support.Through techniques such as machine learning,deep learning,natural language processing,and multimodal fusion,AI provides robust technical support for medical data cleaning,governance,mining,and application.At the data level,intelligent algorithms enable the standardization,structuring,and interoperability of medical data,promoting information sharing across medical systems.At the model level,AI supports auxiliary diagnosis and precision treatment through image recognition,medical record analysis,and knowledge graph construction.At the system level,intelligent decision-support platforms continuously enhance the efficiency and accuracy of healthcare services.However,the widespread adoption of AI in medicine still faces challenges such as privacy protection,data security,model interpretability,and the lack of unified industry standards.Based on a systematic review of AI’s key supporting technologies in medical data processing and application,this paper focuses on the compliance challenges and adaptation strategies during industry integration and proposes an adaptation framework centered on“technological trustworthiness,data security,and industry collaboration.”The study provides theoretical and practical insights for promoting the standardized and sustainable development of AI in the healthcare industry.
