A new method which employs compressive sensing(CS) to reconstruct the sparse spectrum is designed and experimentally demonstrated. On the basis of CS theory, the simulation results indicate that the probability of rec...A new method which employs compressive sensing(CS) to reconstruct the sparse spectrum is designed and experimentally demonstrated. On the basis of CS theory, the simulation results indicate that the probability of reconstruction is high when the step of the sparsity adaptive matching pursuit algorithm is confirmed as 1. Contrastive analysis for four kinds of commonly used measurement matrices: part Hadamard, Bernoulli, Toeplitz and Circular matrix, has been conducted. The results illustrate that the part Hadamard matrix has better performance of reconstruction than the other matrices. The experimental system of the spectral compression reconstruction is mainly based on the digital micro-mirror device(DMD). The experimental results prove that CS can reconstruct sparse spectrum well under the condition of 50% sampling rate. The system error 0.0781 is obtained, which is defined by the average value of the 2-norm. Furthermore, the proposed method shows a dominant ability to discard redundancy.展开更多
Since its emergence in 2009,perovskite photovoltaic technology has achieved remarkable progress,with efficiencies soaring from 3.8%to over 26%.Despite these advancements,challenges such as long-term material and devic...Since its emergence in 2009,perovskite photovoltaic technology has achieved remarkable progress,with efficiencies soaring from 3.8%to over 26%.Despite these advancements,challenges such as long-term material and device stability remain.Addressing these challenges requires reproducible,user-independent laboratory processes and intelligent experimental preselection.Traditional trial-and-error methods and manual analysis are inefficient and urgently need advanced strategies.Automated acceleration platforms have transformed this field by improving efficiency,minimizing errors,and ensuring consistency.This review summarizes recent developments in machine learning-driven auto-mation for perovskite photovoltaics,with a focus on its application in new transport material discovery,composition screening,and device preparation optimization.Furthermore,the review introduces the concept of the self-driven Autonomous Material and Device Acceleration Platforms(AMADAP)labora-tory and discusses potential challenges it may face.This approach streamlines the entire process,from material discovery to device performance improve-ment,ultimately accelerating the development of emerging photovoltaic technologies.展开更多
The disturbance torque generated via solar array drive assembly(SADA) can significantly degrade the key performance of satellite.The discussed SADA is composed of a two-phase hybrid stepping motor and a set of two-sta...The disturbance torque generated via solar array drive assembly(SADA) can significantly degrade the key performance of satellite.The discussed SADA is composed of a two-phase hybrid stepping motor and a set of two-stage straight gear reducer. Firstly, the vibration equation of the two-phase hybrid stepping motor is established via simplifying and linearizing the electromagnetic torque.Secondly, based on the vibration equation established, the disturbance torque model of SADA is created via force analysis and force system simplification. Thirdly, for precisely ground measuring the disturbance torque aroused by SADA, a measurement system,including a strain micro-vibrations measurement platform(SMMP) and a set of gravity unloading device(GUD), is designed.Fourthly, the proposed disturbance torque model is validated by measuring and simulating the disturbance torque produced via SADA driving rigid load through GUD. The results indicate that, the proposed disturbance torque model holds the ability to describe the disturbance torque caused by SADA with high precision. Finally, the disturbance torque emitted by SADA driving a flexible load, designed to simulate solar array, is modeled and simulated via using fixed-interface mode synthesis method(FIMSM). All the conclusions drawn from this article do have a meaningful help for studying the disturbance torque produced by SADA driving solar array on orbit.展开更多
基金supported by the National Natural Science Foundation of China(Nos.61002013 and 11504435)the Natural Science Foundation of Hubei Province(No.2014CFA051)+1 种基金the Key Technology R&D Program of Hubei Province(No.2015BCE048)the Fundamental Research Funds for the Central Universities,South-Central University for Nationalities(Nos.CZY13034,CZW15055 and CZP17026)
文摘A new method which employs compressive sensing(CS) to reconstruct the sparse spectrum is designed and experimentally demonstrated. On the basis of CS theory, the simulation results indicate that the probability of reconstruction is high when the step of the sparsity adaptive matching pursuit algorithm is confirmed as 1. Contrastive analysis for four kinds of commonly used measurement matrices: part Hadamard, Bernoulli, Toeplitz and Circular matrix, has been conducted. The results illustrate that the part Hadamard matrix has better performance of reconstruction than the other matrices. The experimental system of the spectral compression reconstruction is mainly based on the digital micro-mirror device(DMD). The experimental results prove that CS can reconstruct sparse spectrum well under the condition of 50% sampling rate. The system error 0.0781 is obtained, which is defined by the average value of the 2-norm. Furthermore, the proposed method shows a dominant ability to discard redundancy.
基金support of“ELF-PV-Design and development of solution processed functional materials for the next generations of PV technologies”(No.44-6521a/20/4)and“Solar Factory of the Future”(FKZ 20.2-3410.5-4-5)by the Bavarian State Governmentthe German Federal Ministry for Economic Affairs and Climate Action(project Pero4PV,FKZ:03EE1092A)+3 种基金SolMAP and SolarTAP-a Technology Acceleration Platform for emerging Photovoltaics project by Helmholtz Associationsupport from the China Scholarship Council(CSC)support from the Sino-German Postdoc Scholarship Program(CSC-DAAD)support from the Villum Foundation,Grant no.50440.Open Access funding enabled and organized by Projekt DEAL.
文摘Since its emergence in 2009,perovskite photovoltaic technology has achieved remarkable progress,with efficiencies soaring from 3.8%to over 26%.Despite these advancements,challenges such as long-term material and device stability remain.Addressing these challenges requires reproducible,user-independent laboratory processes and intelligent experimental preselection.Traditional trial-and-error methods and manual analysis are inefficient and urgently need advanced strategies.Automated acceleration platforms have transformed this field by improving efficiency,minimizing errors,and ensuring consistency.This review summarizes recent developments in machine learning-driven auto-mation for perovskite photovoltaics,with a focus on its application in new transport material discovery,composition screening,and device preparation optimization.Furthermore,the review introduces the concept of the self-driven Autonomous Material and Device Acceleration Platforms(AMADAP)labora-tory and discusses potential challenges it may face.This approach streamlines the entire process,from material discovery to device performance improve-ment,ultimately accelerating the development of emerging photovoltaic technologies.
文摘The disturbance torque generated via solar array drive assembly(SADA) can significantly degrade the key performance of satellite.The discussed SADA is composed of a two-phase hybrid stepping motor and a set of two-stage straight gear reducer. Firstly, the vibration equation of the two-phase hybrid stepping motor is established via simplifying and linearizing the electromagnetic torque.Secondly, based on the vibration equation established, the disturbance torque model of SADA is created via force analysis and force system simplification. Thirdly, for precisely ground measuring the disturbance torque aroused by SADA, a measurement system,including a strain micro-vibrations measurement platform(SMMP) and a set of gravity unloading device(GUD), is designed.Fourthly, the proposed disturbance torque model is validated by measuring and simulating the disturbance torque produced via SADA driving rigid load through GUD. The results indicate that, the proposed disturbance torque model holds the ability to describe the disturbance torque caused by SADA with high precision. Finally, the disturbance torque emitted by SADA driving a flexible load, designed to simulate solar array, is modeled and simulated via using fixed-interface mode synthesis method(FIMSM). All the conclusions drawn from this article do have a meaningful help for studying the disturbance torque produced by SADA driving solar array on orbit.
