Silicon carbide(SiC) power modules play an essential role in the electric vehicle drive system. To improve their performance, reduce their size, and increase production efficiency, this paper proposes a multiple stake...Silicon carbide(SiC) power modules play an essential role in the electric vehicle drive system. To improve their performance, reduce their size, and increase production efficiency, this paper proposes a multiple staked direct bonded copper(DBC) unit based power module packaging method to parallel more chips. This method utilizes mutual inductance cancellation effect to reduce parasitic inductance. Because the conduction area in the new package is doubled, the overall area of power module can be reduced. Entire power module is divided into smaller units to enhance manufacture yield, and improve design freedom. This paper provides a detailed design, analysis and fabrication procedure for the proposed package structure. Additionally, this paper offers several feasible solutions for the connection between power terminals and DBC untis. With the structure, 18dies were paralleled for each phase-leg in a econodual size power module. Both simulation and double pulse test results demonstrate that, compared to conventional layouts, the proposed package method has 74.8% smaller parasitic inductance and 34.9% lower footprint.展开更多
Light emitting diodes(LEDs)have accounted for most of the lighting market as the technology matures and costs continue to reduce.As a new type of e-waste,LED is a double-edged sword,as it contains not only precious an...Light emitting diodes(LEDs)have accounted for most of the lighting market as the technology matures and costs continue to reduce.As a new type of e-waste,LED is a double-edged sword,as it contains not only precious and rare metals but also organic packaging materials.In previous studies,LED recycling focused on recovering precious and strategic metals while ignoring harmful substances such as organic packaging materials.Unlike crushing and other traditional methods,hydrothermal treatment can provide an environment-friendly process for decomposing packaging materials.This work developed a closed reaction vessel,where the degradation rate of plastic polyphthalamide(PPA)was close to 100%,with nano-TiO_(2)encapsulated in plastic PPA being efficiently recovered,while metals contained in LED were also recycled efficiently.Besides,the role of water in plastic PPA degradation that has been overlooked in current studies was explored and speculated in detail in this work.Environmental impact assessment revealed that the proposed recycling route for waste LED could significantly reduce the overall environmental impact compared to the currently published processes.Especially the developed method could reduce more than half the impact of global warming.Furthermore,this research provides a theoretical basis and a promising method for recycling other plastic-packaged e-waste devices,such as integrated circuits.展开更多
Ensuring high product quality is of paramount importance in pharmaceutical drug manufacturing,as it is subject to rigorous regulatory practices.This study presents a research focused on the development of an on-line d...Ensuring high product quality is of paramount importance in pharmaceutical drug manufacturing,as it is subject to rigorous regulatory practices.This study presents a research focused on the development of an on-line detection method and system for identifying surface defects in pharmaceutical products packaged in aluminum-plastic blisters.Firstly,the aluminum-plastic blister packages exhibit multi-scale features and inter-class indistinction.To address this,the deep semantic network with boundary refinement(DSN-BR)model is proposed,which leverages semantic segmentation domain knowledge,to accurately segment the defects in pixel level.Additionally,a specialized image acquisition module that minimizes the impact of ambient light is established,ensuring high-quality image capture.Finally,the image acquisition module,image detection module,and data management module are designed to construct a comprehensive online surface defect detection system.To validate the effectiveness of our approach,we employ a real dataset for instance verification on the implemented system.The experimental results substantiate the outstanding performance of the DSN-BR,achieving the mean intersection over union(MIoU)of 90.5%.Furthermore,the proposed system achieves an inference speed of up to 14.12 f/s,while attaining an F1-Score of 98.25%.These results demonstrate that the system meets the actual needs of the enterprise and provides theoretical and methodological support for intelligent inspection of product surface quality.By standardizing the control process of pharmaceutical manufacturing and improving the management capability of the manufacturing process,our approach holds significant market application prospects.展开更多
Vehicle interior noise has emerged as a crucial assessment criterion for automotive NVH(Noise,Vibration,and Harshness).When analyzing the NVH performance of the vehicle body,the traditional SEA(Statistical Energy Anal...Vehicle interior noise has emerged as a crucial assessment criterion for automotive NVH(Noise,Vibration,and Harshness).When analyzing the NVH performance of the vehicle body,the traditional SEA(Statistical Energy Analysis)simulation technology is usually limited by the accuracy of the material parameters obtained during the acoustic package modeling and the limitations of the application conditions.In order to effectively solve these shortcomings,based on the analysis of the vehicle noise transmission path,a multi-level objective decomposition architecture of the interior noise at the driver’s right ear is established.Combined with the data-driven method,the ResNet neural network model is introduced.The stacked residual blocks avoid the problem of gradient dis-appearance caused by the increasing network level of the traditional CNN network,thus establishing a higher-precision prediction model.This method alleviates the inherent limitations of traditional SEA simulation design,and enhances the prediction performance of the ResNet model by dynamically adjusting the learning rate.Finally,the proposed method is applied to a specific vehicle model and verified.The results show that the proposed meth-od has significant advantages in prediction accuracy and robustness.展开更多
Bisphenol A (BPA), an important endocrine disruptor, is used in the manufacturing of various materials, including food packaging. Ingestion of contaminated foodstuffs is, in fact, the most relevant form of exposure to...Bisphenol A (BPA), an important endocrine disruptor, is used in the manufacturing of various materials, including food packaging. Ingestion of contaminated foodstuffs is, in fact, the most relevant form of exposure to this substance. However, scarce data on the presence of this contaminant in milk, or whether different types of food packaging influence food contamination are available in Brazil. This study, therefore, aimed to evaluate the BPA contamination of whole milk (fluid and powder) samples packaged in different types of packaging (Tetra Pak?;PET: Poly (ethylene terephthalate;Metallic can (epoxy resin);Polyethylene (PE) and poly (vinylidene chloride) (PVDC);Laminated Film - Metallized Polyester-Polyethylene and glass) and marketed metropolitan region of Rio de Janeiro, Brazil. An analytical method for the BPA determination in milk was optimized for both fluid (pasteurized and ultra-high temperature) and powdered milk samples. A modified QuEChERS method was applied, and BPA determinations were conducted by ultra-performance liquid chromatography coupled with sequential mass spectrometry (HPLC-MS/MS). The validated method was then applied to 51 milk samples, where BPA was detected in five samples (9.8%) and quantified in two (3.8%).展开更多
为解决危大工程中吊装作业安全管理的问题,基于深度学习构建目标检测算法(You Only Look Once version 5,YOLOv5)网络模型,针对进入吊装作业区域内人员的防护装备进行多目标融合检测,并对吊钩在施工过程中的状态进行检测。在原始的检测...为解决危大工程中吊装作业安全管理的问题,基于深度学习构建目标检测算法(You Only Look Once version 5,YOLOv5)网络模型,针对进入吊装作业区域内人员的防护装备进行多目标融合检测,并对吊钩在施工过程中的状态进行检测。在原始的检测网络模型中引入4种注意力机制,并通过5种训练模型的结果对比分析,进而选择卷积块注意力模块(Convolutional Block Attention Module,CBAM)最优模型。优化后的检测模型对安全帽的平均识别精度达86.5%,对反光衣的平均识别精度达83.0%,对吊钩的状态识别精度达92.0%。将训练好的人员检测模型和吊钩检测模型打包成exe执行文件,应用到施工安全管理人员的中控平台,可帮助管理人员更好地判断吊装作业的工作情况,进而及时进行风险管控。展开更多
基金supported in part by National Key R&D Program of China (2021YFB2500600)CAS Youth multi-discipline project (JCTD-2021-09)Strategic Piority Research Program of Chinese Academy of Sciences (XDA28040100)。
文摘Silicon carbide(SiC) power modules play an essential role in the electric vehicle drive system. To improve their performance, reduce their size, and increase production efficiency, this paper proposes a multiple staked direct bonded copper(DBC) unit based power module packaging method to parallel more chips. This method utilizes mutual inductance cancellation effect to reduce parasitic inductance. Because the conduction area in the new package is doubled, the overall area of power module can be reduced. Entire power module is divided into smaller units to enhance manufacture yield, and improve design freedom. This paper provides a detailed design, analysis and fabrication procedure for the proposed package structure. Additionally, this paper offers several feasible solutions for the connection between power terminals and DBC untis. With the structure, 18dies were paralleled for each phase-leg in a econodual size power module. Both simulation and double pulse test results demonstrate that, compared to conventional layouts, the proposed package method has 74.8% smaller parasitic inductance and 34.9% lower footprint.
基金supported by the National Natural Science Foundation of China(52270132).
文摘Light emitting diodes(LEDs)have accounted for most of the lighting market as the technology matures and costs continue to reduce.As a new type of e-waste,LED is a double-edged sword,as it contains not only precious and rare metals but also organic packaging materials.In previous studies,LED recycling focused on recovering precious and strategic metals while ignoring harmful substances such as organic packaging materials.Unlike crushing and other traditional methods,hydrothermal treatment can provide an environment-friendly process for decomposing packaging materials.This work developed a closed reaction vessel,where the degradation rate of plastic polyphthalamide(PPA)was close to 100%,with nano-TiO_(2)encapsulated in plastic PPA being efficiently recovered,while metals contained in LED were also recycled efficiently.Besides,the role of water in plastic PPA degradation that has been overlooked in current studies was explored and speculated in detail in this work.Environmental impact assessment revealed that the proposed recycling route for waste LED could significantly reduce the overall environmental impact compared to the currently published processes.Especially the developed method could reduce more than half the impact of global warming.Furthermore,this research provides a theoretical basis and a promising method for recycling other plastic-packaged e-waste devices,such as integrated circuits.
文摘Ensuring high product quality is of paramount importance in pharmaceutical drug manufacturing,as it is subject to rigorous regulatory practices.This study presents a research focused on the development of an on-line detection method and system for identifying surface defects in pharmaceutical products packaged in aluminum-plastic blisters.Firstly,the aluminum-plastic blister packages exhibit multi-scale features and inter-class indistinction.To address this,the deep semantic network with boundary refinement(DSN-BR)model is proposed,which leverages semantic segmentation domain knowledge,to accurately segment the defects in pixel level.Additionally,a specialized image acquisition module that minimizes the impact of ambient light is established,ensuring high-quality image capture.Finally,the image acquisition module,image detection module,and data management module are designed to construct a comprehensive online surface defect detection system.To validate the effectiveness of our approach,we employ a real dataset for instance verification on the implemented system.The experimental results substantiate the outstanding performance of the DSN-BR,achieving the mean intersection over union(MIoU)of 90.5%.Furthermore,the proposed system achieves an inference speed of up to 14.12 f/s,while attaining an F1-Score of 98.25%.These results demonstrate that the system meets the actual needs of the enterprise and provides theoretical and methodological support for intelligent inspection of product surface quality.By standardizing the control process of pharmaceutical manufacturing and improving the management capability of the manufacturing process,our approach holds significant market application prospects.
基金This research was funded by the SWJTU Science and Technology Innovation Project,Grant Number 2682022CX008the Natural Science Foundation of Sichuan Province,Grant Numbers 2022NSFSC1892,2023NSFSC0395.
文摘Vehicle interior noise has emerged as a crucial assessment criterion for automotive NVH(Noise,Vibration,and Harshness).When analyzing the NVH performance of the vehicle body,the traditional SEA(Statistical Energy Analysis)simulation technology is usually limited by the accuracy of the material parameters obtained during the acoustic package modeling and the limitations of the application conditions.In order to effectively solve these shortcomings,based on the analysis of the vehicle noise transmission path,a multi-level objective decomposition architecture of the interior noise at the driver’s right ear is established.Combined with the data-driven method,the ResNet neural network model is introduced.The stacked residual blocks avoid the problem of gradient dis-appearance caused by the increasing network level of the traditional CNN network,thus establishing a higher-precision prediction model.This method alleviates the inherent limitations of traditional SEA simulation design,and enhances the prediction performance of the ResNet model by dynamically adjusting the learning rate.Finally,the proposed method is applied to a specific vehicle model and verified.The results show that the proposed meth-od has significant advantages in prediction accuracy and robustness.
文摘Bisphenol A (BPA), an important endocrine disruptor, is used in the manufacturing of various materials, including food packaging. Ingestion of contaminated foodstuffs is, in fact, the most relevant form of exposure to this substance. However, scarce data on the presence of this contaminant in milk, or whether different types of food packaging influence food contamination are available in Brazil. This study, therefore, aimed to evaluate the BPA contamination of whole milk (fluid and powder) samples packaged in different types of packaging (Tetra Pak?;PET: Poly (ethylene terephthalate;Metallic can (epoxy resin);Polyethylene (PE) and poly (vinylidene chloride) (PVDC);Laminated Film - Metallized Polyester-Polyethylene and glass) and marketed metropolitan region of Rio de Janeiro, Brazil. An analytical method for the BPA determination in milk was optimized for both fluid (pasteurized and ultra-high temperature) and powdered milk samples. A modified QuEChERS method was applied, and BPA determinations were conducted by ultra-performance liquid chromatography coupled with sequential mass spectrometry (HPLC-MS/MS). The validated method was then applied to 51 milk samples, where BPA was detected in five samples (9.8%) and quantified in two (3.8%).
文摘为解决危大工程中吊装作业安全管理的问题,基于深度学习构建目标检测算法(You Only Look Once version 5,YOLOv5)网络模型,针对进入吊装作业区域内人员的防护装备进行多目标融合检测,并对吊钩在施工过程中的状态进行检测。在原始的检测网络模型中引入4种注意力机制,并通过5种训练模型的结果对比分析,进而选择卷积块注意力模块(Convolutional Block Attention Module,CBAM)最优模型。优化后的检测模型对安全帽的平均识别精度达86.5%,对反光衣的平均识别精度达83.0%,对吊钩的状态识别精度达92.0%。将训练好的人员检测模型和吊钩检测模型打包成exe执行文件,应用到施工安全管理人员的中控平台,可帮助管理人员更好地判断吊装作业的工作情况,进而及时进行风险管控。
