For Printed Circuit Board(PCB)surface defect detection,traditional detection methods mostly focus on template matching-based reference method and manual detections,which have the disadvantages of low defect detection ...For Printed Circuit Board(PCB)surface defect detection,traditional detection methods mostly focus on template matching-based reference method and manual detections,which have the disadvantages of low defect detection efficiency,large errors in defect identification and localization,and low versatility of detectionmethods.In order to furthermeet the requirements of high detection accuracy,real-time and interactivity required by the PCB industry in actual production life.In the current work,we improve the Youonly-look-once(YOLOv4)defect detection method to train and detect six types of PCB small target defects.Firstly,the original Cross Stage Partial Darknet53(CSPDarknet53)backbone network is preserved for PCB defect feature information extraction,and secondly,the original multi-layer cascade fusion method is changed to a single-layer feature layer structure to greatly avoid the problem of uneven distribution of priori anchor boxes size in PCB defect detection process.Then,the K-means++clustering method is used to accurately cluster the anchor boxes to obtain the required size requirements for the defect detection,which further improves the recognition and localization of small PCB defects.Finally,the improved YOLOv4 defect detection model is compared and analyzed on PCB dataset with multi-class algorithms.The experimental results show that the average detection accuracy value of the improved defect detection model reaches 99.34%,which has better detection capability,lower leakage rate and false detection rate for PCB defects in comparison with similar defect detection algorithms.展开更多
The quality of printed circuit board(PCB)micro-hole processing directly determines the stability of the inner and outer circuit connections.Micro-hole drilling technology is a typical method for PCB micro-hole process...The quality of printed circuit board(PCB)micro-hole processing directly determines the stability of the inner and outer circuit connections.Micro-hole drilling technology is a typical method for PCB micro-hole processing.The problem of optimal control of its drilling force is one of the main factors affecting the quality of micro-hole machining.To address this problem,the thrust forces and torques in PCB drilling were first modeled and analyzed,and the corresponding prediction models were established.The drilling force analysis was carried out through the micro-hole drilling experiment,the specific cutting energy under different feed rates was calculated,the influence of the size effect was clarified,and the accuracy of the prediction model was verified.The result shows that during the drilling of glass fiber cloth,changes in the material removal mechanism are induced as the feed per revolution is varied.When the feed per revolution is less than the tool edge radius,the glass fiber is not cut by the main cutting edge,but is crushed and broken.When the feed per revolution is greater than the radius of the tool edge,the glass fiber is cut by the main cutting edge.At the same time,the established analytical model can accurately reflect the influence of the size effect on the drilling torque in PCB micro-hole drilling,and the error is within 10%.This method has certain practical application value in controlling PCB micro hole processing quality.展开更多
A novel low-temperature alkaline smelting process is proposed to convert and separate amphoteric metals in crushed metal enrichment originated from waste printed circuit boards. The central composite design was used t...A novel low-temperature alkaline smelting process is proposed to convert and separate amphoteric metals in crushed metal enrichment originated from waste printed circuit boards. The central composite design was used to optimize the operating parameters,in which mass ratio of Na OH-to-CME, smelting temperature and smelting time were chosen as the variables, and the conversions of amphoteric metals tin, lead, aluminum and zinc were response parameters. Second-order polynomial models of high significance and3 D response surface plots were constructed to show the relationship between the responses and the variables. Optimum area of80%-85% Pb conversion and over 95% Sn conversion was obtained by the overlaid contours at mass ratio of Na OH-to-CME of4.5-5.0, smelting temperature of 653-723 K, smelting time of 90-120 min. The models were validated experimentally in the optimum area, and the results demonstrate that these models are reliable and accurate in predicting the smelting process.展开更多
The recycling of waste printed circuit board(WPCBs) is of great significance for saving resources and protecting the environment. In this study, the WPCBs were pyrolyzed by microwave and the contained valuable metals ...The recycling of waste printed circuit board(WPCBs) is of great significance for saving resources and protecting the environment. In this study, the WPCBs were pyrolyzed by microwave and the contained valuable metals Cu, Sn and Pb were recovered from the pyrolyzed WPCBs. The effect of pyrolysis temperature and time on the recovery efficiency of valuable metals was investigated. Additionally, the characterization for morphology and surface elemental distribution of pyrolysis residues was carried out to investigate the pyrolysis mechanism. The plastic fiber boards turned into black carbides, and they can be easily separated from the metals by manual. The results indicate that 91.2%, 96.1% and 94.4% of Cu, Sn and Pb can be recovered after microwave pyrolysis at 700 °C for 60 minutes. After pyrolysis, about 79.8%(mass)solid products, 11.9%(mass) oil and 8.3%(mass) gas were produced. These gas and oil can be used as fuel and raw materials of organic chemicals, respectively. This process provides an efficient and energy-saving technology for recovering valuable metals from WPCBs.展开更多
Conventional exploding foil initiator (EFI) in ignition or detonation applications hosts many performance advantages, but was hindered by the bulky, inaccurate, inefficient and expensive shortcomings. We highlight a n...Conventional exploding foil initiator (EFI) in ignition or detonation applications hosts many performance advantages, but was hindered by the bulky, inaccurate, inefficient and expensive shortcomings. We highlight a novel micro-chip exploding foil initiator (McEFI) using printed circuit board (PCB) technology. The structural parameters were determined based on energy coupling relationship at the component interfaces. Next, the prototype McEFI has been batch-fabricated using PCB technology, with a monolithic structure of 7.0 mm (l) × 4.5 mm (w) × 4.0 mm (δ). As expected, this PCB-McEFI illustrated the successful firing validations for explosives pellets. This paper has addressed the cost problem in both military munitions and civil markets wherever reliable, insensitive and timing-dependent ignition or detonation are involved.展开更多
The effective recycling of waste printed circuit boards(WPCBs)can conserve resources and reduce environmental pollution.This study explores the pyrolysis and combustion characteristics of WPCBs in various atmospheres ...The effective recycling of waste printed circuit boards(WPCBs)can conserve resources and reduce environmental pollution.This study explores the pyrolysis and combustion characteristics of WPCBs in various atmospheres through thermogravimetric and Gaussian fitting analyses.Furthermore,this study analyses the pyrolysis products and combustion processes of WPCBs through thermogravimetric and Fourier transform infrared analyses(TG-FTIR)and thermogravimetry-mass spectrometry(TG-MS).Results show that the pyrolysis and combustion processes of WPCBs do not constitute a single reaction,but rather an overlap of multiple reactions.The pyrolysis and combustion process of WPCBs is divided into multiple reactions by Gaussian peak fitting.The kinetic parameters of each reaction are obtained by the Coats-Redfern method.In an argon atmosphere,pyrolysis consists of the overlap of the preliminary pyrolysis of epoxy resin,pyrolysis of small organic molecules,and pyrolysis of brominated flame retardants.The thermal decomposition process in the O_(2) atmosphere is mainly divided into two reactions:brominated flame retardant combustion and epoxy combustion.This study provided the theoretical basis for pollution control,process optimization,and reactor design of WPCBs pyrolysis.展开更多
In order to study the role of printed circuit board(PCB)in high-power LED heat dissipation,a simple model of high-power LED lamp was designed.According to this lamp model,some thermal performances such as thermal resi...In order to study the role of printed circuit board(PCB)in high-power LED heat dissipation,a simple model of high-power LED lamp was designed.According to this lamp model,some thermal performances such as thermal resistances of four types of PCB and the changes of LED junction temperature were tested under three different working currents.The obtained results indicate that LED junction temperature can not be lowered significantly with the decreasing thermal resistance of PCB.However,PCB with low thermal resistance can be matched with smaller volume heat sink,so it is hopeful to reduce the size,weight and cost of LED lamp.展开更多
Printed circuit boards(PCBs) contain many toxic substances as well as valuable metals, e.g., lead(Pb) and tin(Sn). In this study, a novel technology, named supergravity, was used to separate different mass ratio...Printed circuit boards(PCBs) contain many toxic substances as well as valuable metals, e.g., lead(Pb) and tin(Sn). In this study, a novel technology, named supergravity, was used to separate different mass ratios of Pb and Sn from Pb–Sn alloys in PCBs. In a supergravity field, the liquid metal phase can permeate from solid particles. Hence, temperatures of 200, 280, and 400°C were chosen to separate Pb and Sn from PCBs. The results depicted that gravity coefficient only affected the recovery rates of Pb and Sn, whereas it had little effect on the mass ratios of Pb and Sn in the obtained alloys. With an increase in gravity coefficient, the recovery values of Pb and Sn in each step of the separation process increased. In the single-step separation process, the mass ratios of Pb and Sn in Pb–Sn alloys were 0.55, 0.40, and 0.64 at 200, 280, and 400°C, respectively. In the two-step separation process, the mass ratios were 0.12 and 0.55 at 280 and 400°C, respectively. Further, the mass ratio was observed to be 0.76 at 400°C in the three-step separation process. This process provides an innovative approach to the recycling mechanism of Pb and Sn from PCBs.展开更多
This paper presents an improved Randomized Circle Detection (RCD) algorithm with the characteristic of circularity to detect randomized circle in images with complex background, which is not based on the Hough Transfo...This paper presents an improved Randomized Circle Detection (RCD) algorithm with the characteristic of circularity to detect randomized circle in images with complex background, which is not based on the Hough Transform. The experimental results denote that this algorithm can locate the circular mark of Printed Circuit Board (PCB).展开更多
In this study,the deformation and stress distribution of printed circuit board(PCB)with different thickness and composite materials under a shock loading were analyzed by the finite element analysis.The standard 8-lay...In this study,the deformation and stress distribution of printed circuit board(PCB)with different thickness and composite materials under a shock loading were analyzed by the finite element analysis.The standard 8-layer PCB subjected to a shock loading 1500 g was evaluated first.Moreover,the finite element models of the PCB with different thickness by stacking various number of layers were discussed.In addition to changing thickness,the core material of PCB was replaced from woven E-glass/epoxy to woven carbon fiber/epoxy for structural enhancement.The non-linear material property of copper foil was considered in the analysis.The results indicated that a thicker PCB has lower stress in the copper foil in PCBs under the shock loading.The stress difference between the thicker PCB(2.6 mm)and thinner PCB(0.6 mm)is around 5%.Using woven carbon fiber/epoxy as core material could lower the stress of copper foil around 6.6%under the shock loading 1500 g for the PCB with 0.6 mm thickness.On the other hand,the stress level is under the failure strength of PCBs with carbon fiber/epoxy core layers and thickness 2.6 mm when the peak acceleration changes from 1500 g to 5000 g.This study could provide a reference for the design and proper applications of the PCB with different thickness and composite materials.展开更多
This paper proposes a corrected method of distorted image based on adaptive control. First, the adaptive control relationship of pixel point positions between distorted image and its corrected image is given by using ...This paper proposes a corrected method of distorted image based on adaptive control. First, the adaptive control relationship of pixel point positions between distorted image and its corrected image is given by using polynomial fitting, thus control point pairs between the distorted image and its corrected image are found. Secondly, the value of both image distortion centre and polynomial coefficient is obtained with least square method, thus the relationship of each control point pairs is deduced. In the course of distortion image processing, the gray value of the corrected image is changed into integer with bilinear interpolation. Finally, the experiments are performed to correct two distorted printed circuit board images. The results are perfect and the mean square errors of residual error are tiny.展开更多
Printed Circuit Boards(PCBs)are very important for proper functioning of any electronic device.PCBs are installed in almost all the electronic device and their functionality is dependent on the perfection of PCBs.If P...Printed Circuit Boards(PCBs)are very important for proper functioning of any electronic device.PCBs are installed in almost all the electronic device and their functionality is dependent on the perfection of PCBs.If PCBs do not function properly then the whole electric machine might fail.So,keeping this in mind researchers are working in this field to develop error free PCBs.Initially these PCBs were examined by the human beings manually,but the human error did not give good results as sometime defected PCBs were categorized as non-defective.So,researchers and experts transformed this manual traditional examination to automated systems.Further to this research image processing and computer vision came into actions where the computer vision experts applied image processing techniques to extract the defects.But,this also did not yield good results.So,to further explore this area Machine Learning and Artificial Intelligence Techniques were applied.In this studywe have appliedDeep Neural Networks to detect the defects in the PCBS.PretrainedVGG16and Inception networkswere applied to extract the relevant features.DeepPCB dataset was used in this study,it has 1500 pairs of both defected and non-defected images.Image pre-processing and data augmentation techniques were applied to increase the training set.Convolution neural networks were applied to classify the test data.The results were compared with state-of-the art technique and it proved that the proposed methodology outperformed it.Performance evaluation metrics were applied to evaluate the proposed methodology.Precision 94.11%,Recall 89.23%,F-Measure 91.91%,and Accuracy 92.67%.展开更多
Automated optical inspection(AOI)is a significant process in printed circuit board assembly(PCBA)production lines which aims to detect tiny defects in PCBAs.Existing AOI equipment has several deficiencies including lo...Automated optical inspection(AOI)is a significant process in printed circuit board assembly(PCBA)production lines which aims to detect tiny defects in PCBAs.Existing AOI equipment has several deficiencies including low throughput,large computation cost,high latency,and poor flexibility,which limits the efficiency of online PCBA inspection.In this paper,a novel PCBA defect detection method based on a lightweight deep convolution neural network is proposed.In this method,the semantic segmentation model is combined with a rule-based defect recognition algorithm to build up a defect detection frame-work.To improve the performance of the model,extensive real PCBA images are collected from production lines as datasets.Some optimization methods have been applied in the model according to production demand and enable integration in lightweight computing devices.Experiment results show that the production line using our method realizes a throughput more than three times higher than traditional methods.Our method can be integrated into a lightweight inference system and pro-mote the flexibility of AOI.The proposed method builds up a general paradigm and excellent example for model design and optimization oriented towards industrial requirements.展开更多
Solder interconnects reliability during drop impact is important for portable electronic products. In this paper, board level drop impact tests were conducted according to the standard of the Joint Electronic Devices ...Solder interconnects reliability during drop impact is important for portable electronic products. In this paper, board level drop impact tests were conducted according to the standard of the Joint Electronic Devices Engineering Council (JEDEC). Solder failure drop numbers were recorded and solder failure analyses were carried out. A high speed data acquisition system was constructed to measure the printed cireuit board ( PCt~ ) dynamic response during the impact. Measured response data were used to characterize the loading feature of the impact. The relatioT~~hip between solder failure features and PCB dynamic response was correlated. Solder failure mechanisms were discussed. The correlation of PCB strain data with the solder failure life indicates that the solder damage accumulated during drop impact is dependent on both strain amplitude and modes contribution of the PCB. Compared with high strain amplitude loading condition, lower strain amplitude with higher mode can even produce more severe damage to the solder interconnects. Repeated impact loadings to the solder induce the combination failure mechanism of both impact and fatigue. Failure analyses results provide convincing verification for the complexity of the failure mechanisms.展开更多
The work presented here focused on the extraction of gold (Au), silver (Ag) and palladium (Pd) from electronic waste using a solution of ammonium thiosulfate. Thiosulfate was used as a valid alternative to cyanide for...The work presented here focused on the extraction of gold (Au), silver (Ag) and palladium (Pd) from electronic waste using a solution of ammonium thiosulfate. Thiosulfate was used as a valid alternative to cyanide for precious metal extractions, due to its non-toxicity and high selectivity. The interactions between sodium thiosulfate, total ammonia/ammonium, precious metal concentrations and the particle size of the waste printed circuit boards (WPCBs) were studied by the response surface methodology (RSM) and the principal component analysis (PCA) to maximize precious metal mobilization. Au extraction reached a high efficiency with a granulometry of less than 0.25 mm, but the consumption of reagents was high. On the other hand, Ag extraction depended neither on thiosulfate/ammonia concentration nor granulometry of WPCBs and it showed efficiency of 90% also with the biggest particle size (0.50 < Ø < 1.00 mm). Pd extraction, similarly to Au, showed the best efficiency with the smallest and the medium WPCB sizes, but required less reagents compared to Au. The results showed that precious metal leaching is a complex process (mainly for Au, which requires more severe conditions in order to achieve high extraction efficiencies) correlated with reagent concentrations, precious metal concentrations and WPCB particle sizes. These results have great potentiality, suggesting the possibility of a more selective recovery of precious metals based on the different granulometry of the WPCBs. Furthermore, the high extraction efficiencies obtained for all the metals bode well in the perspective of large-scale applications.展开更多
The printed circuit board(PCB)is an indispensable component of electronic products,which deter-mines the quality of these products.With the development and advancement of manufacturing technology,the layout and struct...The printed circuit board(PCB)is an indispensable component of electronic products,which deter-mines the quality of these products.With the development and advancement of manufacturing technology,the layout and structure of PCB are getting complicated.However,there are few effective and accurate PCB defect detection methods.There are high requirements for the accuracy of PCB defect detection in the actual pro-duction environment,so we propose two PCB defect detection frameworks with multiple model fusion including the defect detection by multi-model voting method(DDMV)and the defect detection by multi-model learning method(DDML).With the purpose of reducing wrong and missing detection,the DDMV and DDML integrate multiple defect detection networks with different fusion strategies.The effectiveness and accuracy of the proposed framework are verified with extensive experiments on two open-source PCB datasets.The experimental results demonstrate that the proposed DDMV and DDML are better than any other individual state-of-the-art PCB defect detection model in F1-score,and the area under curve value of DDML is also higher than that of any other individual detection model.Furthermore,compared with DDMV,the DDML with an automatic machine learning method achieves the best performance in PCB defect detection,and the Fl-score on the two datasets can reach 99.7%and 95.6%respectively.展开更多
For Automatic Optical Inspection (AOI) machines that were introduced to Printed Circuit Board market more than five years ago, illumination technique and light devices are outdated. Images captured by old AO...For Automatic Optical Inspection (AOI) machines that were introduced to Printed Circuit Board market more than five years ago, illumination technique and light devices are outdated. Images captured by old AOI machines are not easy to be recognized by typical optical character recognition (OCR) algorithms, especially for dark silk. How to effectively increase silk recognition accuracy is indispensable for improving overall production efficiency in SMT plant. This paper uses fine tuned Character Region Awareness for Text Detection (CRAFT) method to build model for dark silk recognition. CRAFT model consists of a structure similar to U-net, followed by VGG based convolutional neural network. Continuous two-dimensional Gaussian distribution was used for the annotation of image segmentation. CRAFT model is good at recognizing different types of printed characters with high accuracy and transferability. Results show that with the help of CRAFT model, accuracy for OK board is 95% (error rate is 5%), and accuracy for NG board is 100% (omission rate is 0%).展开更多
Printed circuit boards (PCBs) are in all electronic equipment, so with the sharp increase of electronic waste, the recovery of PCB components has become a critical research field. This paper presents a study of the ...Printed circuit boards (PCBs) are in all electronic equipment, so with the sharp increase of electronic waste, the recovery of PCB components has become a critical research field. This paper presents a study of the reclaimation and reuse of nonmetallic materials recovered from waste PCBs. Mechanical processes, such as crushing, milling, and separation, were used to process waste PCBs. Nonmetallic materials in the PCBs were separated using density-based separation with separation rates in excess of 95%. The recovered nonmetals were used to make models, construction materials, composite boards, sewer grates, and amusement park boats. The PCB nonmetal products have better mechanical characteristics and durability than traditional materials and fillers. The flexural strength of the PCB nonmetallic material composite boards is 30% greater than that of standard products. Products derived from PCB waste processing have been brought into industrial production. The study shows that PCB nonmetals can be reused in profitable and environmentally friendly ways.展开更多
Triggered spark-gap switch is a popular discharge switch for pulse power systems.Previous studies have focused on planarizing this switch using thin film techniques in order to meet the requirements of compact size in...Triggered spark-gap switch is a popular discharge switch for pulse power systems.Previous studies have focused on planarizing this switch using thin film techniques in order to meet the requirements of compact size in the systems.Such switches are one-shot due to electrodes being too thin to sufficiently resist spark-erosion.Additionally,these switches did not employ any structures in securing internal gas composition,resulting in inconsistent performance under harsh atmospheres.In this work,a novel planar triggered spark-gap switch(PTS)with a hermetically sealed cavity was batched-prepared with printed circuit board(PCB)technology,to achieve reusability with low cost.The proposed PTS was inspected by micro-computed tomography to ensure PCB techniques meet the requirements of machining precision.The results from electrical experiments demonstrated that PCB PTS were consistent and reusable with lifespan over 20 times.The calculated switch voltage and circuit current were consistent with those derived from real-world measurements.Finally,PCB PTS was used to introduce hexanitrostilbene(HNS)pellets in a pulse power system to verify its performance.展开更多
The recycling method and principle of SnO2 from the tin slag of printed circuit boards(PCB) waste were investigated. In this study, pure SnO2 powders were obtained through a multi-step process including ball-milling...The recycling method and principle of SnO2 from the tin slag of printed circuit boards(PCB) waste were investigated. In this study, pure SnO2 powders were obtained through a multi-step process including ball-milling, roasting, dissolving, precipitating, and pickling. The total recovery rate of tin can be up to 91 %. The SnO2 powders obtained is the single phase, and the content of SnO2 is up to 99.9 %. However, the SnO2 particles are easier to agglomerate during the precipitation process. The agglomerate SnO2 particles are about 7.778 lm in mean particle size(D50). This preparation method presents a viable alternative for the tin slag recycling. The tin is not only recycled, but also reused directly to prepare pure SnO2 powders.展开更多
基金This work was funded by the Natural Science Research Project of Higher Education Institutions in Jiangsu Province(No.20KJA520007)Min Zhang receives the grant and the URLs to sponsors’websites are http://jyt.jiangsu.gov.cn/.
文摘For Printed Circuit Board(PCB)surface defect detection,traditional detection methods mostly focus on template matching-based reference method and manual detections,which have the disadvantages of low defect detection efficiency,large errors in defect identification and localization,and low versatility of detectionmethods.In order to furthermeet the requirements of high detection accuracy,real-time and interactivity required by the PCB industry in actual production life.In the current work,we improve the Youonly-look-once(YOLOv4)defect detection method to train and detect six types of PCB small target defects.Firstly,the original Cross Stage Partial Darknet53(CSPDarknet53)backbone network is preserved for PCB defect feature information extraction,and secondly,the original multi-layer cascade fusion method is changed to a single-layer feature layer structure to greatly avoid the problem of uneven distribution of priori anchor boxes size in PCB defect detection process.Then,the K-means++clustering method is used to accurately cluster the anchor boxes to obtain the required size requirements for the defect detection,which further improves the recognition and localization of small PCB defects.Finally,the improved YOLOv4 defect detection model is compared and analyzed on PCB dataset with multi-class algorithms.The experimental results show that the average detection accuracy value of the improved defect detection model reaches 99.34%,which has better detection capability,lower leakage rate and false detection rate for PCB defects in comparison with similar defect detection algorithms.
基金National Natural Science Foundation of China(No.51805079)Fundamental Research Funds for the Central Universities,China(No.2232021D-15)Shanghai Science and Technology Program(No.20DZ2251400)。
文摘The quality of printed circuit board(PCB)micro-hole processing directly determines the stability of the inner and outer circuit connections.Micro-hole drilling technology is a typical method for PCB micro-hole processing.The problem of optimal control of its drilling force is one of the main factors affecting the quality of micro-hole machining.To address this problem,the thrust forces and torques in PCB drilling were first modeled and analyzed,and the corresponding prediction models were established.The drilling force analysis was carried out through the micro-hole drilling experiment,the specific cutting energy under different feed rates was calculated,the influence of the size effect was clarified,and the accuracy of the prediction model was verified.The result shows that during the drilling of glass fiber cloth,changes in the material removal mechanism are induced as the feed per revolution is varied.When the feed per revolution is less than the tool edge radius,the glass fiber is not cut by the main cutting edge,but is crushed and broken.When the feed per revolution is greater than the radius of the tool edge,the glass fiber is cut by the main cutting edge.At the same time,the established analytical model can accurately reflect the influence of the size effect on the drilling torque in PCB micro-hole drilling,and the error is within 10%.This method has certain practical application value in controlling PCB micro hole processing quality.
基金Projects(51074190,51234009)supported by the National Natural Science Foundation of ChinaProject(2014DFA90520)supported by International Cooperation Program of Ministry of Science of ChinaProject(20110162110049)supported by the Doctoral Scientific Fund Project of the Ministry of Education of China
文摘A novel low-temperature alkaline smelting process is proposed to convert and separate amphoteric metals in crushed metal enrichment originated from waste printed circuit boards. The central composite design was used to optimize the operating parameters,in which mass ratio of Na OH-to-CME, smelting temperature and smelting time were chosen as the variables, and the conversions of amphoteric metals tin, lead, aluminum and zinc were response parameters. Second-order polynomial models of high significance and3 D response surface plots were constructed to show the relationship between the responses and the variables. Optimum area of80%-85% Pb conversion and over 95% Sn conversion was obtained by the overlaid contours at mass ratio of Na OH-to-CME of4.5-5.0, smelting temperature of 653-723 K, smelting time of 90-120 min. The models were validated experimentally in the optimum area, and the results demonstrate that these models are reliable and accurate in predicting the smelting process.
基金supported by the National Key Research and Development Program of China (2019YFC1908404)the National Natural Science Foundation of China (Nos. 51834008, 51874040,52034002)+1 种基金the Guangxi Innovation-Driven Development Project(AA18242042-1)the Fundamental Research Funds for the Central Universities (FRF-TP-18-020A3)。
文摘The recycling of waste printed circuit board(WPCBs) is of great significance for saving resources and protecting the environment. In this study, the WPCBs were pyrolyzed by microwave and the contained valuable metals Cu, Sn and Pb were recovered from the pyrolyzed WPCBs. The effect of pyrolysis temperature and time on the recovery efficiency of valuable metals was investigated. Additionally, the characterization for morphology and surface elemental distribution of pyrolysis residues was carried out to investigate the pyrolysis mechanism. The plastic fiber boards turned into black carbides, and they can be easily separated from the metals by manual. The results indicate that 91.2%, 96.1% and 94.4% of Cu, Sn and Pb can be recovered after microwave pyrolysis at 700 °C for 60 minutes. After pyrolysis, about 79.8%(mass)solid products, 11.9%(mass) oil and 8.3%(mass) gas were produced. These gas and oil can be used as fuel and raw materials of organic chemicals, respectively. This process provides an efficient and energy-saving technology for recovering valuable metals from WPCBs.
基金We gratefully acknowledge the support from National Natural Science Foundation of China(Grant No.22075145).
文摘Conventional exploding foil initiator (EFI) in ignition or detonation applications hosts many performance advantages, but was hindered by the bulky, inaccurate, inefficient and expensive shortcomings. We highlight a novel micro-chip exploding foil initiator (McEFI) using printed circuit board (PCB) technology. The structural parameters were determined based on energy coupling relationship at the component interfaces. Next, the prototype McEFI has been batch-fabricated using PCB technology, with a monolithic structure of 7.0 mm (l) × 4.5 mm (w) × 4.0 mm (δ). As expected, this PCB-McEFI illustrated the successful firing validations for explosives pellets. This paper has addressed the cost problem in both military munitions and civil markets wherever reliable, insensitive and timing-dependent ignition or detonation are involved.
基金financially supported by the National Key R&D Program of China(Nos.2019YFC1908400 and 2019YFC1907405)the National Natural Science Foundation of China(Nos.51904124,51804139,52004111 and 52074136)+2 种基金the Jiangxi Provincial Cultivation Program for Academic and Technical Leaders of Major Subjects(Nos.20212BCJL23052 and 20212BCJ23007)the Distinguished Professor Program of Jinggang Scholars,China Institutions of Higher Learning Jiangxi Province,the Science and Technology Research Project of the Jiangxi Provincial Department of Education(No.gjj170507)the Science Research Foundation of Jiangxi University of Science and Technology(No.jxxjbs 17046)。
文摘The effective recycling of waste printed circuit boards(WPCBs)can conserve resources and reduce environmental pollution.This study explores the pyrolysis and combustion characteristics of WPCBs in various atmospheres through thermogravimetric and Gaussian fitting analyses.Furthermore,this study analyses the pyrolysis products and combustion processes of WPCBs through thermogravimetric and Fourier transform infrared analyses(TG-FTIR)and thermogravimetry-mass spectrometry(TG-MS).Results show that the pyrolysis and combustion processes of WPCBs do not constitute a single reaction,but rather an overlap of multiple reactions.The pyrolysis and combustion process of WPCBs is divided into multiple reactions by Gaussian peak fitting.The kinetic parameters of each reaction are obtained by the Coats-Redfern method.In an argon atmosphere,pyrolysis consists of the overlap of the preliminary pyrolysis of epoxy resin,pyrolysis of small organic molecules,and pyrolysis of brominated flame retardants.The thermal decomposition process in the O_(2) atmosphere is mainly divided into two reactions:brominated flame retardant combustion and epoxy combustion.This study provided the theoretical basis for pollution control,process optimization,and reactor design of WPCBs pyrolysis.
基金Special Fund Project of Science and Technology Innovation of Dongli District(21090302)Research Projectof Applied Basic and Front Technologies of Tianjin(10JCZDJC15400)
文摘In order to study the role of printed circuit board(PCB)in high-power LED heat dissipation,a simple model of high-power LED lamp was designed.According to this lamp model,some thermal performances such as thermal resistances of four types of PCB and the changes of LED junction temperature were tested under three different working currents.The obtained results indicate that LED junction temperature can not be lowered significantly with the decreasing thermal resistance of PCB.However,PCB with low thermal resistance can be matched with smaller volume heat sink,so it is hopeful to reduce the size,weight and cost of LED lamp.
基金financially supported by the National Natural Science Foundation of China (No. 51704022)
文摘Printed circuit boards(PCBs) contain many toxic substances as well as valuable metals, e.g., lead(Pb) and tin(Sn). In this study, a novel technology, named supergravity, was used to separate different mass ratios of Pb and Sn from Pb–Sn alloys in PCBs. In a supergravity field, the liquid metal phase can permeate from solid particles. Hence, temperatures of 200, 280, and 400°C were chosen to separate Pb and Sn from PCBs. The results depicted that gravity coefficient only affected the recovery rates of Pb and Sn, whereas it had little effect on the mass ratios of Pb and Sn in the obtained alloys. With an increase in gravity coefficient, the recovery values of Pb and Sn in each step of the separation process increased. In the single-step separation process, the mass ratios of Pb and Sn in Pb–Sn alloys were 0.55, 0.40, and 0.64 at 200, 280, and 400°C, respectively. In the two-step separation process, the mass ratios were 0.12 and 0.55 at 280 and 400°C, respectively. Further, the mass ratio was observed to be 0.76 at 400°C in the three-step separation process. This process provides an innovative approach to the recycling mechanism of Pb and Sn from PCBs.
基金supported by Science and Technology Project of Fujian Provincial Department of Education under contract JAT170917Youth Science and Research Foundation of Chengyi College Jimei University under contract C16005.
文摘This paper presents an improved Randomized Circle Detection (RCD) algorithm with the characteristic of circularity to detect randomized circle in images with complex background, which is not based on the Hough Transform. The experimental results denote that this algorithm can locate the circular mark of Printed Circuit Board (PCB).
基金the support from Ministry of Science and Technology,Taiwan,R.O.C.,through grant MOST-105-2221-E-007-031-MY3.
文摘In this study,the deformation and stress distribution of printed circuit board(PCB)with different thickness and composite materials under a shock loading were analyzed by the finite element analysis.The standard 8-layer PCB subjected to a shock loading 1500 g was evaluated first.Moreover,the finite element models of the PCB with different thickness by stacking various number of layers were discussed.In addition to changing thickness,the core material of PCB was replaced from woven E-glass/epoxy to woven carbon fiber/epoxy for structural enhancement.The non-linear material property of copper foil was considered in the analysis.The results indicated that a thicker PCB has lower stress in the copper foil in PCBs under the shock loading.The stress difference between the thicker PCB(2.6 mm)and thinner PCB(0.6 mm)is around 5%.Using woven carbon fiber/epoxy as core material could lower the stress of copper foil around 6.6%under the shock loading 1500 g for the PCB with 0.6 mm thickness.On the other hand,the stress level is under the failure strength of PCBs with carbon fiber/epoxy core layers and thickness 2.6 mm when the peak acceleration changes from 1500 g to 5000 g.This study could provide a reference for the design and proper applications of the PCB with different thickness and composite materials.
基金Project supported by the Research Foundation of the State Key Laboratory,China(Grant No.9140C1406020708)the Program Research Foundation of Hunan Province Science-Technology Department,China(Grant No.2009FJ3187)the 11th Five Year Plan for Key Construction Academic Subject(Optics)of Hunan Province,China(Grant No.06GXCD02)
文摘This paper proposes a corrected method of distorted image based on adaptive control. First, the adaptive control relationship of pixel point positions between distorted image and its corrected image is given by using polynomial fitting, thus control point pairs between the distorted image and its corrected image are found. Secondly, the value of both image distortion centre and polynomial coefficient is obtained with least square method, thus the relationship of each control point pairs is deduced. In the course of distortion image processing, the gray value of the corrected image is changed into integer with bilinear interpolation. Finally, the experiments are performed to correct two distorted printed circuit board images. The results are perfect and the mean square errors of residual error are tiny.
基金The author would like to thank Deanship of Scientific Research at Shaqra University for their support to carry this work.
文摘Printed Circuit Boards(PCBs)are very important for proper functioning of any electronic device.PCBs are installed in almost all the electronic device and their functionality is dependent on the perfection of PCBs.If PCBs do not function properly then the whole electric machine might fail.So,keeping this in mind researchers are working in this field to develop error free PCBs.Initially these PCBs were examined by the human beings manually,but the human error did not give good results as sometime defected PCBs were categorized as non-defective.So,researchers and experts transformed this manual traditional examination to automated systems.Further to this research image processing and computer vision came into actions where the computer vision experts applied image processing techniques to extract the defects.But,this also did not yield good results.So,to further explore this area Machine Learning and Artificial Intelligence Techniques were applied.In this studywe have appliedDeep Neural Networks to detect the defects in the PCBS.PretrainedVGG16and Inception networkswere applied to extract the relevant features.DeepPCB dataset was used in this study,it has 1500 pairs of both defected and non-defected images.Image pre-processing and data augmentation techniques were applied to increase the training set.Convolution neural networks were applied to classify the test data.The results were compared with state-of-the art technique and it proved that the proposed methodology outperformed it.Performance evaluation metrics were applied to evaluate the proposed methodology.Precision 94.11%,Recall 89.23%,F-Measure 91.91%,and Accuracy 92.67%.
基金supported in part by the IoT Intelligent Microsystem Center of Tsinghua University-China Mobile Joint Research Institute.
文摘Automated optical inspection(AOI)is a significant process in printed circuit board assembly(PCBA)production lines which aims to detect tiny defects in PCBAs.Existing AOI equipment has several deficiencies including low throughput,large computation cost,high latency,and poor flexibility,which limits the efficiency of online PCBA inspection.In this paper,a novel PCBA defect detection method based on a lightweight deep convolution neural network is proposed.In this method,the semantic segmentation model is combined with a rule-based defect recognition algorithm to build up a defect detection frame-work.To improve the performance of the model,extensive real PCBA images are collected from production lines as datasets.Some optimization methods have been applied in the model according to production demand and enable integration in lightweight computing devices.Experiment results show that the production line using our method realizes a throughput more than three times higher than traditional methods.Our method can be integrated into a lightweight inference system and pro-mote the flexibility of AOI.The proposed method builds up a general paradigm and excellent example for model design and optimization oriented towards industrial requirements.
基金Supported by National Natural Science Foundation of China (No. 51075107 No. 51174069) and Key Project of Natural Science Foundation of Heilongjiang Province (No. ZD200910).
文摘Solder interconnects reliability during drop impact is important for portable electronic products. In this paper, board level drop impact tests were conducted according to the standard of the Joint Electronic Devices Engineering Council (JEDEC). Solder failure drop numbers were recorded and solder failure analyses were carried out. A high speed data acquisition system was constructed to measure the printed cireuit board ( PCt~ ) dynamic response during the impact. Measured response data were used to characterize the loading feature of the impact. The relatioT~~hip between solder failure features and PCB dynamic response was correlated. Solder failure mechanisms were discussed. The correlation of PCB strain data with the solder failure life indicates that the solder damage accumulated during drop impact is dependent on both strain amplitude and modes contribution of the PCB. Compared with high strain amplitude loading condition, lower strain amplitude with higher mode can even produce more severe damage to the solder interconnects. Repeated impact loadings to the solder induce the combination failure mechanism of both impact and fatigue. Failure analyses results provide convincing verification for the complexity of the failure mechanisms.
文摘The work presented here focused on the extraction of gold (Au), silver (Ag) and palladium (Pd) from electronic waste using a solution of ammonium thiosulfate. Thiosulfate was used as a valid alternative to cyanide for precious metal extractions, due to its non-toxicity and high selectivity. The interactions between sodium thiosulfate, total ammonia/ammonium, precious metal concentrations and the particle size of the waste printed circuit boards (WPCBs) were studied by the response surface methodology (RSM) and the principal component analysis (PCA) to maximize precious metal mobilization. Au extraction reached a high efficiency with a granulometry of less than 0.25 mm, but the consumption of reagents was high. On the other hand, Ag extraction depended neither on thiosulfate/ammonia concentration nor granulometry of WPCBs and it showed efficiency of 90% also with the biggest particle size (0.50 < Ø < 1.00 mm). Pd extraction, similarly to Au, showed the best efficiency with the smallest and the medium WPCB sizes, but required less reagents compared to Au. The results showed that precious metal leaching is a complex process (mainly for Au, which requires more severe conditions in order to achieve high extraction efficiencies) correlated with reagent concentrations, precious metal concentrations and WPCB particle sizes. These results have great potentiality, suggesting the possibility of a more selective recovery of precious metals based on the different granulometry of the WPCBs. Furthermore, the high extraction efficiencies obtained for all the metals bode well in the perspective of large-scale applications.
基金the Natural Science Foundation of Shanghai(No.20ZR1420400)the State Key Program of National Natural Science Foundation of China(No.61936001)。
文摘The printed circuit board(PCB)is an indispensable component of electronic products,which deter-mines the quality of these products.With the development and advancement of manufacturing technology,the layout and structure of PCB are getting complicated.However,there are few effective and accurate PCB defect detection methods.There are high requirements for the accuracy of PCB defect detection in the actual pro-duction environment,so we propose two PCB defect detection frameworks with multiple model fusion including the defect detection by multi-model voting method(DDMV)and the defect detection by multi-model learning method(DDML).With the purpose of reducing wrong and missing detection,the DDMV and DDML integrate multiple defect detection networks with different fusion strategies.The effectiveness and accuracy of the proposed framework are verified with extensive experiments on two open-source PCB datasets.The experimental results demonstrate that the proposed DDMV and DDML are better than any other individual state-of-the-art PCB defect detection model in F1-score,and the area under curve value of DDML is also higher than that of any other individual detection model.Furthermore,compared with DDMV,the DDML with an automatic machine learning method achieves the best performance in PCB defect detection,and the Fl-score on the two datasets can reach 99.7%and 95.6%respectively.
文摘For Automatic Optical Inspection (AOI) machines that were introduced to Printed Circuit Board market more than five years ago, illumination technique and light devices are outdated. Images captured by old AOI machines are not easy to be recognized by typical optical character recognition (OCR) algorithms, especially for dark silk. How to effectively increase silk recognition accuracy is indispensable for improving overall production efficiency in SMT plant. This paper uses fine tuned Character Region Awareness for Text Detection (CRAFT) method to build model for dark silk recognition. CRAFT model consists of a structure similar to U-net, followed by VGG based convolutional neural network. Continuous two-dimensional Gaussian distribution was used for the annotation of image segmentation. CRAFT model is good at recognizing different types of printed characters with high accuracy and transferability. Results show that with the help of CRAFT model, accuracy for OK board is 95% (error rate is 5%), and accuracy for NG board is 100% (omission rate is 0%).
基金the National High-Tech Research and Development (863) Program of China (No. 2004AA420120)
文摘Printed circuit boards (PCBs) are in all electronic equipment, so with the sharp increase of electronic waste, the recovery of PCB components has become a critical research field. This paper presents a study of the reclaimation and reuse of nonmetallic materials recovered from waste PCBs. Mechanical processes, such as crushing, milling, and separation, were used to process waste PCBs. Nonmetallic materials in the PCBs were separated using density-based separation with separation rates in excess of 95%. The recovered nonmetals were used to make models, construction materials, composite boards, sewer grates, and amusement park boats. The PCB nonmetal products have better mechanical characteristics and durability than traditional materials and fillers. The flexural strength of the PCB nonmetallic material composite boards is 30% greater than that of standard products. Products derived from PCB waste processing have been brought into industrial production. The study shows that PCB nonmetals can be reused in profitable and environmentally friendly ways.
基金We gratefully acknowledge support from the Natural Science Foundation of Jiangsu Province of China(Grant No.BK20151486).
文摘Triggered spark-gap switch is a popular discharge switch for pulse power systems.Previous studies have focused on planarizing this switch using thin film techniques in order to meet the requirements of compact size in the systems.Such switches are one-shot due to electrodes being too thin to sufficiently resist spark-erosion.Additionally,these switches did not employ any structures in securing internal gas composition,resulting in inconsistent performance under harsh atmospheres.In this work,a novel planar triggered spark-gap switch(PTS)with a hermetically sealed cavity was batched-prepared with printed circuit board(PCB)technology,to achieve reusability with low cost.The proposed PTS was inspected by micro-computed tomography to ensure PCB techniques meet the requirements of machining precision.The results from electrical experiments demonstrated that PCB PTS were consistent and reusable with lifespan over 20 times.The calculated switch voltage and circuit current were consistent with those derived from real-world measurements.Finally,PCB PTS was used to introduce hexanitrostilbene(HNS)pellets in a pulse power system to verify its performance.
基金financially supported by the Beijing Nova Program (No. Z141103001814006)the National Key Technology R&D Program (Nos. 2012BAC12B05 and 2012BAC02B01)+1 种基金the National Natural Science Foundation of China (Nos. 51174247 and U1360202)the National High-Tech Research and the Development Program of China (No. 2012AA063202)
文摘The recycling method and principle of SnO2 from the tin slag of printed circuit boards(PCB) waste were investigated. In this study, pure SnO2 powders were obtained through a multi-step process including ball-milling, roasting, dissolving, precipitating, and pickling. The total recovery rate of tin can be up to 91 %. The SnO2 powders obtained is the single phase, and the content of SnO2 is up to 99.9 %. However, the SnO2 particles are easier to agglomerate during the precipitation process. The agglomerate SnO2 particles are about 7.778 lm in mean particle size(D50). This preparation method presents a viable alternative for the tin slag recycling. The tin is not only recycled, but also reused directly to prepare pure SnO2 powders.