This paper presents a simulation model to predict the power generation of p-n junction-based beta... more This paper presents a simulation model to predict the power generation of p-n junction-based betavoltaic devices. The model provides two key aspects of information for device evaluation: electron-hole pair generation rate and device power output. A Monte-Carlo model was used to simulate generation rate and the device performance was simulated using the generation rate with Synopsys ® Medici. We investigated the effects of the temperature, semiconductor materials with different bandgap energies (Si, Ge and SiC) and different isotope sources (Ni-63 and tritium) on the performance of betavoltaic microbatteries. Our simulation results indicate that a homojunction structure with wide bandgap semiconductor is more favorable for betavoltaic device performance. A simple wide bandgap p-n junction cell with an embedded radioisotope source could be the most promising candidate for betavoltaic applications.
FPGA structures are common designed in Serial structure and Parallel structure. As the most effic... more FPGA structures are common designed in Serial structure and Parallel structure. As the most efficient one, Parallel structure also could be divided into whole-parallel and half-parallel which we called pipe-line structure. Whole Parallel structure FPGA take a great advantage on speed but consuming enormous resources. Moreover, FFT cannot give enough details on Time-frequency domain. In order to avoid these disadvantages, proposed STFT processer plan on FPGA. Based on the research on algorithms STFT, we gave an improved pipeline structure FPGA design. Then this design implied high speed STFT which take both speed and precision into count on FPGA. At the last of this paper, we conducted signal test. In this step , any signals were all collected from actual work condition. And then verify the feasibility of the program through simulation and actual signal test.
We have investigated the electronic structure of graphene under different planar strain distribut... more We have investigated the electronic structure of graphene under different planar strain distributions using the first-principles pseudopotential plane-wave method and the tight-binding approach. We found that graphene with a symmetrical strain distribution is always a zero band-gap semiconductor and its pseudogap decreases linearly with the strain strength in the elastic regime. However, asymmetrical strain distributions in graphene result in opening of band gaps at the Fermi level. For the graphene with a strain distribution parallel to CC bonds, its band gap continuously increases to its maximum width of 0.486 eV as the strain increases up to 12.2%. For the graphene with a strain distribution perpendicular to CC bonds, its band gap continuously increases only to its maximum width of 0.170 eV as the strain increases up to 7.3%. The anisotropic nature of graphene is also reflected by different Poisson ratios under large strains in different directions. We found that the Poisson ratio approaches to a constant of 0.1732 under small strains but decreases differently under large strains along different directions.
Abstract Acoustic-based diagnosis (ABD) is a promising method for machinery fault detection due t... more Abstract Acoustic-based diagnosis (ABD) is a promising method for machinery fault detection due to its ability of non-contact measurement by air-couple. However, most of the ABD methods are constrained by strong and highly non-stationary background noise interference in practical industrial application. To address the shortcoming, a novel anti-noise ABD method based on recursive attention mechanism (RAM) is proposed in this paper. In proposed method, a multi-stage attention module (MSAM) is firstly designed as fundament of RAM to automatically estimate the noise interference probability within time–frequency (T-F) unit of each signal sample. Simultaneously, a recursive learning strategy is introduced to construct RAM by reusing the MSAM for multiple blocks to gradually refine the estimated probability and adaptively simulated noise interference in diagnosis model for enhancing anti-noise diagnosis ability. Then, based on RAM, a domain adaption method is established to endow the model with good cross-domain ability for further improving the anti-noise performance of the diagnosis model. The experiment result in both real-industrial noise condition and stimulated noise conditions with different SNRs indicate that the proposed method has stronger robustness and better generalization ability than other popular methods in dealing with gear fault diagnosis task under noise condition.
This paper presents a simulation model to predict the power generation of p-n junction-based beta... more This paper presents a simulation model to predict the power generation of p-n junction-based betavoltaic devices. The model provides two key aspects of information for device evaluation: electron-hole pair generation rate and device power output. A Monte-Carlo model was used to simulate generation rate and the device performance was simulated using the generation rate with Synopsys ® Medici. We investigated the effects of the temperature, semiconductor materials with different bandgap energies (Si, Ge and SiC) and different isotope sources (Ni-63 and tritium) on the performance of betavoltaic microbatteries. Our simulation results indicate that a homojunction structure with wide bandgap semiconductor is more favorable for betavoltaic device performance. A simple wide bandgap p-n junction cell with an embedded radioisotope source could be the most promising candidate for betavoltaic applications.
FPGA structures are common designed in Serial structure and Parallel structure. As the most effic... more FPGA structures are common designed in Serial structure and Parallel structure. As the most efficient one, Parallel structure also could be divided into whole-parallel and half-parallel which we called pipe-line structure. Whole Parallel structure FPGA take a great advantage on speed but consuming enormous resources. Moreover, FFT cannot give enough details on Time-frequency domain. In order to avoid these disadvantages, proposed STFT processer plan on FPGA. Based on the research on algorithms STFT, we gave an improved pipeline structure FPGA design. Then this design implied high speed STFT which take both speed and precision into count on FPGA. At the last of this paper, we conducted signal test. In this step , any signals were all collected from actual work condition. And then verify the feasibility of the program through simulation and actual signal test.
We have investigated the electronic structure of graphene under different planar strain distribut... more We have investigated the electronic structure of graphene under different planar strain distributions using the first-principles pseudopotential plane-wave method and the tight-binding approach. We found that graphene with a symmetrical strain distribution is always a zero band-gap semiconductor and its pseudogap decreases linearly with the strain strength in the elastic regime. However, asymmetrical strain distributions in graphene result in opening of band gaps at the Fermi level. For the graphene with a strain distribution parallel to CC bonds, its band gap continuously increases to its maximum width of 0.486 eV as the strain increases up to 12.2%. For the graphene with a strain distribution perpendicular to CC bonds, its band gap continuously increases only to its maximum width of 0.170 eV as the strain increases up to 7.3%. The anisotropic nature of graphene is also reflected by different Poisson ratios under large strains in different directions. We found that the Poisson ratio approaches to a constant of 0.1732 under small strains but decreases differently under large strains along different directions.
Abstract Acoustic-based diagnosis (ABD) is a promising method for machinery fault detection due t... more Abstract Acoustic-based diagnosis (ABD) is a promising method for machinery fault detection due to its ability of non-contact measurement by air-couple. However, most of the ABD methods are constrained by strong and highly non-stationary background noise interference in practical industrial application. To address the shortcoming, a novel anti-noise ABD method based on recursive attention mechanism (RAM) is proposed in this paper. In proposed method, a multi-stage attention module (MSAM) is firstly designed as fundament of RAM to automatically estimate the noise interference probability within time–frequency (T-F) unit of each signal sample. Simultaneously, a recursive learning strategy is introduced to construct RAM by reusing the MSAM for multiple blocks to gradually refine the estimated probability and adaptively simulated noise interference in diagnosis model for enhancing anti-noise diagnosis ability. Then, based on RAM, a domain adaption method is established to endow the model with good cross-domain ability for further improving the anti-noise performance of the diagnosis model. The experiment result in both real-industrial noise condition and stimulated noise conditions with different SNRs indicate that the proposed method has stronger robustness and better generalization ability than other popular methods in dealing with gear fault diagnosis task under noise condition.
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