In order to improve the evaluation process of inverter open-circuit faults diagnosis in permanent magnet synchronous motor(PMSM)drives,this paper presents a diagnosis method based on current residuals and machine lear...In order to improve the evaluation process of inverter open-circuit faults diagnosis in permanent magnet synchronous motor(PMSM)drives,this paper presents a diagnosis method based on current residuals and machine learning models.The machine learning models are introduced to make a comprehensive evaluation for the current residuals obtained from a state observer,instead of evaluating the residuals by comparing with thresholds.Meanwhile,fault diagnosis and location are conducted simultaneously by the machine learning models,which simplifies the diagnosis process.Besides,a sampling strategy is designed to implement the proposed scheme online.Experiments are carried out on a DSP based PMSM drive,and the effectiveness of the proposed method is verified.展开更多
The length of the sgRNA-DNA complementary sequence is a key factor influencing the cleavage activity of Streptococcus pyogenes Cas9(SpCas9)and its variants.The detailed mechanism remains unknown.Here,based on in vitro...The length of the sgRNA-DNA complementary sequence is a key factor influencing the cleavage activity of Streptococcus pyogenes Cas9(SpCas9)and its variants.The detailed mechanism remains unknown.Here,based on in vitro cleavage assays and base editing analysis,we demonstrate that reducing the length of this complementary region can confer nickase activity on SpCas9 and eSpCas9(1.1).We also show that these nicks are made on the target DNA strand.These properties encouraged us to develop a dual-functional system that simultaneously carries out double-strand DNA cleavage and C-to-T base conversions at separate targets.This system provides a novel tool for achieving trait stacking in plants.展开更多
文摘In order to improve the evaluation process of inverter open-circuit faults diagnosis in permanent magnet synchronous motor(PMSM)drives,this paper presents a diagnosis method based on current residuals and machine learning models.The machine learning models are introduced to make a comprehensive evaluation for the current residuals obtained from a state observer,instead of evaluating the residuals by comparing with thresholds.Meanwhile,fault diagnosis and location are conducted simultaneously by the machine learning models,which simplifies the diagnosis process.Besides,a sampling strategy is designed to implement the proposed scheme online.Experiments are carried out on a DSP based PMSM drive,and the effectiveness of the proposed method is verified.
基金supported by grants from the Strategic Priority Research Program of the Chinese Academy of Sciences(Precision Seed Design and Breeding,XDA24020102)the National Transgenic Science and Technology Program(2018ZX0801002B)+2 种基金the National Natural Science Foundation of China(31788103 and 31971370)the Chinese Academy of Sciences(QYZDY-SSW-SMC030)the National Key R&D Program of China(2018YFA0900600,2016YFD0100102-11,and 2016YFD0100605)。
文摘The length of the sgRNA-DNA complementary sequence is a key factor influencing the cleavage activity of Streptococcus pyogenes Cas9(SpCas9)and its variants.The detailed mechanism remains unknown.Here,based on in vitro cleavage assays and base editing analysis,we demonstrate that reducing the length of this complementary region can confer nickase activity on SpCas9 and eSpCas9(1.1).We also show that these nicks are made on the target DNA strand.These properties encouraged us to develop a dual-functional system that simultaneously carries out double-strand DNA cleavage and C-to-T base conversions at separate targets.This system provides a novel tool for achieving trait stacking in plants.
