Southeast University

Other

Nanjing University of Aeronautics and Astronautics

Nr Electric Co., Ltd

Nr Engineering Co., Ltd

Harman Internatioanl Industries, Incorporated

Harman International Industries, Inc.

Nr Electric Engineering Co., Ltd.

Kai Wang

Peng Cao

Zeng Yang

Wei Li

Jun Chen

Jianjun Ma

Xudong Wang

Xianxu Huo

Shiqian Ma

Guodong Li

Qixue Zhang

Guang Wang

Yan Qi

Tai Yang

Lei Wu

Huazhong Li

Jingjing Yan

Ke Xu

Jinguang Hao

Lu Sun

Wenjiang Pei

Jun Jiang

Tianchun Xiang

Qianqian Song

Chaohai Zhang

Wei Bao

Zigang Guo

Yifan Bie

Jiasheng Chen

Judong Chen

Aidong Zeng

Qingshan Xu

Baoguo Zhao

Honglei Zhao

Ling Jiang

Honglin Wang

Yao Wang

An optimization method for a digital integrated circuit is provided. Under the precondition of satisfying certain timing constraints, circuit-level, path-level and gate cell-level features of a circuit are extracted to construct a leakage power optimization model, and optimization data from commercial circuit optimization tools is used to train the model to predict voltage threshold types of gate cells after circuit optimization, such that the circuit can be optimized by adjusting voltage thresholds of gate cells in a post-routing gate-level netlist, thus realizing the optimization objective of reducing leakage power.

Optimization method for digital integrated circuit

Disclosed in the present invention is a method for predicting a delay at multiple corners for a digital integrated circuit, which is applicable to the problem of timing signoff at multiple corners. In the aspect of feature engineering, a path delay relationship at adjacent corners is extracted by using a dilated convolutional neural network (Dilated CNN), and learning is performed by using a bi-directional long short-term memory model (Bi-directional Long Short-Term Memory, BLSTM) to obtain topology information of a path. Finally, prediction results of a path delay at a plurality of corners are obtained by using an output of a multi-gate mixture-of-experts network model (Multi-gate Mixture-of-Experts, MMoE). Compared with a conventional machine learning method, the present invention can achieve prediction with higher precision through more effective feature engineering processing in a case of low simulation overheads, and is of great significance for timing signoff at multiple corners of a digital integrated circuit.

Method for predicting delay at multiple corners for digital integrated circuit

The present invention discloses a method for quickly eliminating ferromagnetic resonance of a voltage transformer. The method includes: first sampling a three-phase voltage and an open-delta voltage of a voltage transformer; calculating a flux linkage corresponding to a zero-sequence voltage by means of an integral algorithm; and when detecting that ferromagnetic resonance occurs in the mutual inductor, further checking whether the absolute value of the flux linkage corresponding to the zero-sequence voltage or the absolute value of the open-delta voltage respectively falls within a set range, and if yes, starting a secondary resonance elimination loop for resonance elimination. The present invention also discloses a corresponding device for quickly eliminating ferromagnetic resonance of a voltage transformer. The present method and device accurately analyze and control resonance elimination trigger time based on a conventional secondary resonance elimination principle, and can effectively eliminate the impact of the core saturation of a voltage transformer on a resonance elimination process, thereby greatly improving the success probability of single resonance elimination.

Method and device for quickly eliminating ferromagnetic resonance of voltage transformer

The invention relates to a method for real-time scheduling of multi-energy complementary micro-grids based on a Rollout algorithm, which is technically characterized by comprising the following steps of: Step 1, setting up a moving-horizon Markov decision process model for the real-time scheduling of the multi-energy complementary micro-grids with random new-energy outputs, and establishing constraint conditions for the real-time scheduling; Step 2, establishing a target function of the real-time scheduling; Step 3, dividing a single complete scheduling cycle into a plurality of scheduling intervals, and finding one basic feasible solution meeting the constraint conditions for the real-time scheduling based on a greedy algorithm; and Step 4, finding a solution to the moving-horizon Markov decision process model for the real-time scheduling of the multi-energy complementary micro-grids by using the Rollout algorithm based on the basic feasible solution from Step 3. With the consideration of the fluctuations in the new-energy outputs, the present invention solves the problems of low speed and low efficiency of a traditional algorithm at the same time, enabling high-speed efficient multi-energy complementary micro-grid real-time scheduling.

Method for real-time scheduling of multi-energy complementary micro-grids based on rollout algorithm

The present disclosure relates to an optical fiber detection device for detecting a discharge fault of a high-voltage bushing, which includes an optical fiber sensing unit, an optical fiber delay unit, a photoelectric conversion unit, and a signal collecting and processing unit. The optical fiber sensing unit includes sensing optical fibers; the optical fiber delay unit includes delay optical fibers, a light source, and couplers; the photoelectric conversion unit includes a photodetector; the signal collecting and processing unit includes a high-pass filter. The delay optical fibers are connected to the couplers; an output end of the light source is connected to the light-splitting coupler; an input end of the photodetector is connected to the light-splitting coupler, and an output end of the photodetector is connected to the signal collecting and processing unit; and the light-combining coupler is connected to the sensing optical fibers.

Optical fiber detection device for detecting discharge fault of high-voltage bushing

A fine timing method is provided. The method comprises: calculating values of a first timing metric function based on cross-correlation between a received signal and M training sequences within a time period, to obtain a plurality of sets of X values spaced according to a certain pattern; calculating summations for the plurality of sets of X values, respectively; and determining the beginning of a data frame based on the calculated summations.

Fine timing

Growing community of inventors

Nanjing, China

Kai Wang