Machine learning(ML)methods have been extensively applied to optimize additive manufacturing(AM)process parameters.However,existing studies predominantly focus on the relationship between processing parameters and pro...Machine learning(ML)methods have been extensively applied to optimize additive manufacturing(AM)process parameters.However,existing studies predominantly focus on the relationship between processing parameters and properties for specifc alloys,thus limiting their applicability to a broader range of materials.To address this issue,dimensionless parameters,which can be easily calculated from simple analytical expressions,were used as inputs to construct an ML model for classifying the relative density in laser-powder bed fusion.The model was trained using data from four widely used alloys collected from literature.The accuracy and generalizability of the trained model were validated using two laser-powder bed fusion(L-PBF)high-entropy alloys that were not included in the training process.The results demonstrate that the accuracy scores for both cases exceed 0.8.Moreover,the simple dimensionless inputs in the present model can be calculated conveniently without numerical simulations,thereby facilitating the recommendation of process parameters.展开更多
In order to obtain better inverse synthetic aperture radar(ISAR)image,a novel structure-enhanced spatial spectrum is proposed for estimating the incoherence parameters and fusing multiband.The proposed method takes fu...In order to obtain better inverse synthetic aperture radar(ISAR)image,a novel structure-enhanced spatial spectrum is proposed for estimating the incoherence parameters and fusing multiband.The proposed method takes full advantage of the original electromagnetic scattering data and its conjugated form by combining them with the novel covariance matrices.To analyse the superiority of the modified algorithm,the mathematical expression of equivalent signal to noise ratio(SNR)is derived,which can validate our proposed algorithm theoretically.In addition,compared with the conventional matrix pencil(MP)algorithm and the conventional root-multiple signal classification(Root-MUSIC)algorithm,the proposed algorithm has better parameter estimation performance and more accurate multiband fusion results at the same SNR situations.Validity and effectiveness of the proposed algorithm is demonstrated by simulation data and real radar data.展开更多
Because the hydraulic directional valve usually works in a bad working environment and is disturbed by multi-factor noise,the traditional single sensor monitoring technology is difficult to use for an accurate diagnos...Because the hydraulic directional valve usually works in a bad working environment and is disturbed by multi-factor noise,the traditional single sensor monitoring technology is difficult to use for an accurate diagnosis of it.Therefore,a fault diagnosis method based on multi-sensor information fusion is proposed in this paper to reduce the inaccuracy and uncertainty of traditional single sensor information diagnosis technology and to realize accurate monitoring for the location or diagnosis of early faults in such valves in noisy environments.Firstly,the statistical features of signals collected by the multi-sensor are extracted and the depth features are obtained by a convolutional neural network(CNN)to form a complete and stable multi-dimensional feature set.Secondly,to obtain a weighted multi-dimensional feature set,the multi-dimensional feature sets of similar sensors are combined,and the entropy weight method is used to weight these features to reduce the interference of insensitive features.Finally,the attention mechanism is introduced to improve the dual-channel CNN,which is used to adaptively fuse the weighted multi-dimensional feature sets of heterogeneous sensors,to flexibly select heterogeneous sensor information so as to achieve an accurate diagnosis.Experimental results show that the weighted multi-dimensional feature set obtained by the proposed method has a high fault-representation ability and low information redundancy.It can diagnose simultaneously internal wear faults of the hydraulic directional valve and electromagnetic faults of actuators that are difficult to diagnose by traditional methods.This proposed method can achieve high fault-diagnosis accuracy under severe working conditions.展开更多
Light detection and ranging(LiDAR)has contributed immensely to forest mapping and 3D tree modelling.From the perspective of data acquisition,the integration of LiDAR data from different platforms would enrich forest i...Light detection and ranging(LiDAR)has contributed immensely to forest mapping and 3D tree modelling.From the perspective of data acquisition,the integration of LiDAR data from different platforms would enrich forest information at the tree and plot levels.This research develops a general framework to integrate ground-based and UAV-LiDAR(ULS)data to better estimate tree parameters based on quantitative structure modelling(QSM).This is accomplished in three sequential steps.First,the ground-based/ULS LiDAR data were co-registered based on the local density peaks of the clustered canopy.Next,redundancy and noise were removed for the ground-based/ULS LiDAR data fusion.Finally,tree modeling and biophysical parameter retrieval were based on QSM.Experiments were performed for Backpack/Handheld/UAV-based multi-platform mobile LiDAR data of a subtropical forest,including poplar and dawn redwood species.Generally,ground-based/ULS LiDAR data fusion outperforms ground-based LiDAR with respect to tree parameter estimation compared to field data.The fusion-derived tree height,tree volume,and crown volume significantly improved by up to 9.01%,5.28%,and 18.61%,respectively,in terms of rRMSE.By contrast,the diameter at breast height(DBH)is the parameter that has the least benefits from fusion,and rRMSE remains approximately the same,because stems are already well sampled from ground data.Additionally,particularly for dense forests,the fusion-derived tree parameters were improved compared to those derived from ground-based LiDAR.Ground-based LiDAR can potentially be used to estimate tree parameters in low-stand-density forests,whereby the improvement owing to fusion is not significant.展开更多
·AIM:To assess the reproducibility of macular perfusion parameters in non-proliferative diabetic retinopathy(NPDR)patients measured by different examiners and two different sweep modes of optical coherence tomogr...·AIM:To assess the reproducibility of macular perfusion parameters in non-proliferative diabetic retinopathy(NPDR)patients measured by different examiners and two different sweep modes of optical coherence tomography angiography(OCTA).·METHODS:Ninety-eight(98 eyes)patients with NPDR were included in this study.All participates were performed three times using Cirrus OCTA with Angiography 3×3 mm^(2)and 6×6 mm^(2)sweep mode by two examiners.The macular foveal avascular zone(FAZ)and vessel density(VD)in the superficial retinal layer(SRL)were measured.The reproducibility of the measurements was evaluated with intraclass correlation coefficients(ICC)and coefficient of variation(CoV).·RESULTS:The intra-mode ICCs of Angiography 3×3 mm^(2)and 6×6 mm^(2)sweep mode were 0.957 to 0.959 and 0.964 to 0.977,respectively;and the inter-mode ICCs were 0.962 to 0.970.The intra-examiner ICCs of macular perfusion parameters were>0.950;and the inter-examiner ICCs were0.928 to 0.969.All CoVs were<1.0%.·CONCLUSION:Cirrus OCTA can measure macular perfusion parameters in NPDR patients with excellent reproducibility.The measurements of FAZ and VD in the SRL determined by Angiography 3×3 mm^(2)and 6×6 mm^(2)sweep mode are highly consistent and both sweep modes are suitable for macular perfusion parameters measurement.展开更多
BACKGROUND Improving the sagittal lumbar-pelvic parameters after fusion surgery is important for improving clinical outcomes.The impact of midline lumbar fusion(MIDLF)on sagittal lumbar-pelvic alignment for the manage...BACKGROUND Improving the sagittal lumbar-pelvic parameters after fusion surgery is important for improving clinical outcomes.The impact of midline lumbar fusion(MIDLF)on sagittal lumbar-pelvic alignment for the management of degenerative lumbar diseases is still unknown.AIM To analyze the effects of short-segment MIDLF and minimally invasive transforaminal lumbar interbody fusion(MIS-TLIF)on sagittal lumbar-pelvic parameters.METHODS We retrospectively analyzed 63 patients with degenerative lumbar diseases who underwent single-segment MIDLF or MIS-TLIF.The imaging data of patients were collected before surgery and at the final follow-up.The radiological sagittal parameters included the lumbar lordosis(LL),lower LL,L4 slope(L4S),L5 slope(L5S),L5 incidence(L5I),L1 axis and S1 distance(LASD),pelvic incidence(PI),pelvic tilt(PT),sacral slope(SS),and PI-LL mismatch(PI-LL).Additionally,the clinical outcomes,including lower back and leg pain visual analog scale(VAS)and Oswestry disability index(ODI)scores,were also analyzed.RESULTS In both groups,LL and Lower LL significantly increased,while L5I and LASD significantly decreased at the final follow-up compared to that recorded prior to operation(P<0.05).In the MIDLF group,L4S significantly decreased compared to that recorded prior to operation(P<0.05),while the mean SS significantly increased and the PT significantly decreased compared to that recorded prior to operation(P<0.05).In the MIS-TLIF group,SS slightly increased and the mean PT value decreased compared to that recorded prior to operation,but without a statistically significant difference(P>0.05).However,the PI-LL in both groups was significantly reduced compared to that recorded prior to operation(P<0.05).There was no significant difference in the sagittal lumbar-pelvic parameters between the two groups prior to operation and at the final follow-up(P>0.05).In addition,the change in sagittal lumbar-pelvic parameters did not differ significantly,except forΔLASD within the two groups(P>0.05).The mean lower back and leg pain VAS and ODI scores in both groups were significantly improved three months after surgery and at the final follow-up.Though the mean ODI score in the MIDLF group three months after surgery was slightly higher than that in the MIS-TLIF group,there was no significant difference between the two groups at the final follow-up.CONCLUSION Short-segment MIDLF and MIS-TLIF can equally improve sagittal lumbar parameters such as LL,Lower LL,L5I,and LASD in the treatment of lumbar degenerative diseases.However,MIDLF had a larger impact on pelvic parameters than MIS-TLIF.展开更多
An algorithm of highly maneuvering target tracking is proposed to solve the problem of large tracking error caused by strong maneuver. In this algorithm, a new estimator, named as multi-parameter fusion Singer (MF-Sin...An algorithm of highly maneuvering target tracking is proposed to solve the problem of large tracking error caused by strong maneuver. In this algorithm, a new estimator, named as multi-parameter fusion Singer (MF-Singer) model is derived based on the Singer model and the fuzzy reasoning method by using radial acceleration and velocity of the target, and applied to the problem of maneuvering target tracking in strong maneuvering environment and operating environment. The tracking performance of the MF-Singer model is evaluated and compared with other manuevering tracking models. It is shown that the MF-Singer model outperforms these algorithms in several examples.展开更多
Medical image fusion has been developed as an efficient assistive technology in various clinical applications such as medical diagnosis and treatment planning.Aiming at the problem of insufficient protection of image ...Medical image fusion has been developed as an efficient assistive technology in various clinical applications such as medical diagnosis and treatment planning.Aiming at the problem of insufficient protection of image contour and detail information by traditional image fusion methods,a new multimodal medical image fusion method is proposed.This method first uses non-subsampled shearlet transform to decompose the source image to obtain high and low frequency subband coefficients,then uses the latent low rank representation algorithm to fuse the low frequency subband coefficients,and applies the improved PAPCNN algorithm to fuse the high frequency subband coefficients.Finally,based on the automatic setting of parameters,the optimization method configuration of the time decay factorαe is carried out.The experimental results show that the proposed method solves the problems of difficult parameter setting and insufficient detail protection ability in traditional PCNN algorithm fusion images,and at the same time,it has achieved great improvement in visual quality and objective evaluation indicators.展开更多
Multimodal medical image fusion can help physicians provide more accurate treatment plans for patients, as unimodal images provide limited valid information. To address the insufficient ability of traditional medical ...Multimodal medical image fusion can help physicians provide more accurate treatment plans for patients, as unimodal images provide limited valid information. To address the insufficient ability of traditional medical image fusion solutions to protect image details and significant information, a new multimodality medical image fusion method(NSST-PAPCNNLatLRR) is proposed in this paper. Firstly, the high and low-frequency sub-band coefficients are obtained by decomposing the source image using NSST. Then, the latent low-rank representation algorithm is used to process the low-frequency sub-band coefficients;An improved PAPCNN algorithm is also proposed for the fusion of high-frequency sub-band coefficients. The improved PAPCNN model was based on the automatic setting of the parameters, and the optimal method was configured for the time decay factor αe. The experimental results show that, in comparison with the five mainstream fusion algorithms, the new algorithm has significantly improved the visual effect over the comparison algorithm,enhanced the ability to characterize important information in images, and further improved the ability to protect the detailed information;the new algorithm has achieved at least four firsts in six objective indexes.展开更多
The accurate estimation of parameters is the premise for establishing a high-fidelity simulation model of a valve-controlled cylinder system.Bench test data are easily obtained,but it is challenging to emulate actual ...The accurate estimation of parameters is the premise for establishing a high-fidelity simulation model of a valve-controlled cylinder system.Bench test data are easily obtained,but it is challenging to emulate actual loads in the research on parameter estimation of valve-controlled cylinder system.Despite the actual load information contained in the operating data of the control valve,its acquisition remains challenging.This paper proposes a method that fuses bench test and operating data for parameter estimation to address the aforementioned problems.The proposed method is based on Bayesian theory,and its core is a pool fusion of prior information from bench test and operating data.Firstly,a system model is established,and the parameters in the model are analysed.Secondly,the bench and operating data of the system are collected.Then,the model parameters and weight coefficients are estimated using the data fusion method.Finally,the estimated effects of the data fusion method,Bayesian method,and particle swarm optimisation(PSO)algorithm on system model parameters are compared.The research shows that the weight coefficient represents the contribution of different prior information to the parameter estimation result.The effect of parameter estimation based on the data fusion method is better than that of the Bayesian method and the PSO algorithm.Increasing load complexity leads to a decrease in model accuracy,highlighting the crucial role of the data fusion method in parameter estimation studies.展开更多
As a typical laser additive manufacturing technology,laser powder bed fusion(LPBF)has achieved demonstration applications in aerospace,biomedical and other fields.However,how to select process parameters quickly and r...As a typical laser additive manufacturing technology,laser powder bed fusion(LPBF)has achieved demonstration applications in aerospace,biomedical and other fields.However,how to select process parameters quickly and reasonably is still themain concern of LPBF production.In order to quantitatively analyze the influence of different process parameters(laser power,scanning speed,hatch space and layer thickness)on the LPBF process,the multilayer and multi-path forming process of LPBF was predicted based on the open-source discrete element method framework Yade and the open-source finite volume method framework OpenFOAM.Based on the design of experiments method,a four-factor three-level orthogonal test scheme was designed,and the porosity and surface roughness data of each calculation scheme were extracted.By analyzing the orthogonal test data,it was found that as the laser power increased,the porosity decreased,and as the scanning speed,hatch space,and layer thickness increased,the porosity increased.In addition,the influence of laser power and scanning speed on surface roughness showed a trend of decreasing first and then increasing,while the influence of scanning distance and layer thickness on surface roughness showed amonotonous increasing trend.The order of the influence of each process parameter on porosity was:scanning speed>laying thickness>laser power>hatch space,and the order of the influence of each process parameter on surface roughness was:hatch space>layer thickness>laser power>scanning speed.So the porosity of the part is most sensitive to scanning speed,and the surface roughness is the most sensitive to hatch space.The above conclusions are expected to provide process control basis for actual LPBF production of the 316L stainless steel alloy.展开更多
Intelligence and perception are two operative technologies in 6G scenarios.The intelligent wireless network and information perception require a deep fusion of artificial intelligence(AI)and wireless communications in...Intelligence and perception are two operative technologies in 6G scenarios.The intelligent wireless network and information perception require a deep fusion of artificial intelligence(AI)and wireless communications in 6G systems.Therefore,fusion is becoming a typical feature and key challenge of 6G wireless communication systems.In this paper,we focus on the critical issues and propose three application scenarios in 6G wireless systems.Specifically,we first discuss the fusion of AI and 6G networks for the enhancement of 5G-advanced technology and future wireless communication systems.Then,we introduce the wireless AI technology architecture with 6G multidimensional information perception,which includes the physical layer technology of multi-dimensional feature information perception,full spectrum fusion technology,and intelligent wireless resource management.The discussion of key technologies for intelligent 6G wireless network networks is expected to provide a guideline for future research.展开更多
The successful confinement of the arc by the flux band depends on the welding process parameters for achieving single-pass,multi-layer, and ultra-narrow gap welding. The sidewall fusion depth, the width of the heat-af...The successful confinement of the arc by the flux band depends on the welding process parameters for achieving single-pass,multi-layer, and ultra-narrow gap welding. The sidewall fusion depth, the width of the heat-affected zone, and the line energy are utilized as comprehensive indications of the quality of the welded joint. In order to achieve well fusion and reduce the heat input to the base metal.Three welding process characteristics were chosen as the primary determinants, including welding voltage, welding speed, and wire feeding speed. The metamodel of the welding quality index was built by the orthogonal experiments. The metamodel and NSGA-Ⅱ(Non-dominated sorting genetic algorithm Ⅱ) were combined to develop a multi-objective optimization model of ultra-narrow gap welding process parameters. The results showed that the optimized welding process parameters can increase the sidewall fusion depth, reduce the width of the heataffected zone and the line energy, and to some extent improve the overall quality of the ultra-narrow gap welding process.展开更多
This paper starts with untime-diversification of the time-diversification deformation model and gives displacement distribution model of untime-diversification and simplifies further the study of deformation model. Th...This paper starts with untime-diversification of the time-diversification deformation model and gives displacement distribution model of untime-diversification and simplifies further the study of deformation model. The paper discusses the problem of least squares fitting of coordinate parameters model—parameters of deformation model. During discussion, the basic means of cubic B splines and two steps of multidimensional disorder datum fitting are adopted which can make fitting function calculated mostly approximate coordinate parameters model and it can make calculation easier.展开更多
Transpiration cooling is crucial for the performance of aerospace engine components,relying heavily on the processing quality and accuracy of microchannels.Laser powder bed fusion(LPBF)offers the potential for integra...Transpiration cooling is crucial for the performance of aerospace engine components,relying heavily on the processing quality and accuracy of microchannels.Laser powder bed fusion(LPBF)offers the potential for integrated manufacturing of complex parts and precise microchannel fabrication,essential for engine cooling applications.However,optimizing LPBF’s extensive process parameters to control processing quality and microchannel accuracy effectively remains a significant challenge,especially given the time-consuming and labor-intensive nature of handling numerous variables and the need for thorough data analysis and correlation discovery.This study introduced a combined methodology of high-throughput experiments and Gaussian process algorithms to optimize the processing quality and accuracy of nickel-based high-temperature alloy with microchannel structures.250 parameter combinations,including laser power,scanning speed,channel diameter,and spot compensation,were designed across ten high-throughput specimens.This setup allowed for rapid and efficient evaluation of processing quality and microchannel accuracy.Employing Bayesian optimization,the Gaussian process model accurately predicted processing outcomes over a broad parameter range.The correlation between various processing parameters,processing quality and accuracy was revealed,and various optimized process combinations were summarized.Verification through computed Tomography testing of the specimens confirmed the effectiveness and precision of this approach.The approach introduced in this research provides a way for quickly and efficiently optimizing the process parameters and establishing process-property relationships for LPBF,which has broad application value.展开更多
Laser powder-bed fusion(LPBF)of Zn-0.8Cu(wt.%)alloys exhibits significant advantages in the customization of biodegradable bone implants.However,the formability of LPBFed Zn alloy is not sufficient due to the spheroid...Laser powder-bed fusion(LPBF)of Zn-0.8Cu(wt.%)alloys exhibits significant advantages in the customization of biodegradable bone implants.However,the formability of LPBFed Zn alloy is not sufficient due to the spheroidization during the interaction of powder and laser beam,of which the mechanism is still not well understood.In this study,the evolution of morphology and grain structure of the LPBFed Zn-Cu alloy was investigated based on single-track deposition experiments.As the scanning speed increases,the grain structure of a single track of Zn-Cu alloy gradually refines,but the formability deteriorates,leading to the defect’s formation in the subsequent fabrication.The Zn-Cu alloys fabricated by optimum processing parameters exhibit a tensile strength of 157.13 MPa,yield strength of 106.48 MPa and elongation of 14.7%.This work provides a comprehensive understanding of the processing optimization of Zn-Cu alloy,achieving LPBFed Zn-Cu alloy with high density and excellent mechanical properties.展开更多
Powder bed fusion(PBF)in metallic additive manufacturing offers the ability to produce intricate geometries,high-strength components,and reliable products.However,powder processing before energy-based binding signific...Powder bed fusion(PBF)in metallic additive manufacturing offers the ability to produce intricate geometries,high-strength components,and reliable products.However,powder processing before energy-based binding significantly impacts the final product’s integrity.Processing maps guide efficient process design to minimize defects,but creating them through experimentation alone is challenging due to the wide range of parameters,necessitating a comprehensive computational parametric analysis.In this study,we used the discrete element method to parametrically analyze the powder processing design space in PBF of stainless steel 316L powders.Uniform lattice parameter sweeps are often used for parametric analysis,but are computationally intensive.We find that non-uniform parameter sweep based on the low discrepancy sequence(LDS)algorithm is ten times more efficient at exploring the design space while accurately capturing the relationship between powder flow dynamics and bed packing density.We introduce a multi-layer perceptron(MLP)model to interpolate parametric causalities within the LDS parameter space.With over 99%accuracy,it effectively captures these causalities while requiring fewer simulations.Finally,we generate processing design maps for machine setups and powder selections for efficient process design.We find that recoating speed has the highest impact on powder processing quality,followed by recoating layer thickness,particle size,and inter-particle friction.展开更多
采用激光粉末床熔融(laser powder bed fusion,LPBF)技术制备K418B高温合金,利用光学显微镜、扫描电镜和硬度仪分析工艺参数激光功率(140~220 W)和扫描速度(600~1400 mm/s)对显微缺陷、致密度、微观组织及硬度的影响。结果表明,激光功...采用激光粉末床熔融(laser powder bed fusion,LPBF)技术制备K418B高温合金,利用光学显微镜、扫描电镜和硬度仪分析工艺参数激光功率(140~220 W)和扫描速度(600~1400 mm/s)对显微缺陷、致密度、微观组织及硬度的影响。结果表明,激光功率和扫描速度均显著影响样品的相对密度与缺陷分布。低能量密度易产生不规则孔洞,高能量密度则易形成球形气孔与凝固裂纹;体积能量密度(volume energy density,VED)过低或过高都会降低致密度和性能。最佳工艺参数为激光功率180 W、扫描速度1400 mm/s,在该条件下样品致密度可达99.95%以上,表面缺陷少,仅有少量凝固裂纹,显微组织呈明显熔池边界和胞状结构,维氏硬度达366.8HV_(0.2)。微观组织观察显示,熔池边界处晶粒较粗大,内部可见细胞状柱状晶,局部连续跨越多个熔池,表现出快速凝固特征。硬度随VED先升后降,与孔隙含量及致密度变化一致。研究揭示热应力是裂纹产生的主要原因,为K418B合金LPBF成形的参数优化提供依据,对提升航空发动机关键部件制造质量具有工程应用价值。展开更多
Flexible sensing array integrated with multiple sensors is an attractive approach for flight parameter detection.However,the poor resolution of flexible sensors and time-consuming neural network processes mitigate the...Flexible sensing array integrated with multiple sensors is an attractive approach for flight parameter detection.However,the poor resolution of flexible sensors and time-consuming neural network processes mitigate their accuracy and adaptability in predicting flight parameters.Here we present an ultra-thin flexible sensing patch with a new configuration,comprising a differential pressure sensor array and a vector flow velocity sensor.The capacitive differential pressure sensor array is fabricated by a multilayer polyimide bonding technique,reaching a resolution of 0.14 Pa.To solve flight parameters with the flexible sensing patch,we develop an analytical pressure-velocity fusion algorithm,enabling fast response and high accuracy in flight parameter detection.The average errors in calculating the angle of attack,angle of sideslip,and airspeed are 0.22°,0.35°,and 0.73 m s^(-1),respectively.The high-resolution flexible sensors and novel analytical pressure-velocity fusion algorithm pave the way for flexible sensing patch-based air data sensing techniques.展开更多
基金supported by the National Key R&D Program of China(Grant No.2023YFB4606502)the National Natural Science Foundation of China(Grant No.52471017)the Research Fund of the State Key Laboratory of Solidification Processing(NPU),China(Grant No.2020-TS-06).
文摘Machine learning(ML)methods have been extensively applied to optimize additive manufacturing(AM)process parameters.However,existing studies predominantly focus on the relationship between processing parameters and properties for specifc alloys,thus limiting their applicability to a broader range of materials.To address this issue,dimensionless parameters,which can be easily calculated from simple analytical expressions,were used as inputs to construct an ML model for classifying the relative density in laser-powder bed fusion.The model was trained using data from four widely used alloys collected from literature.The accuracy and generalizability of the trained model were validated using two laser-powder bed fusion(L-PBF)high-entropy alloys that were not included in the training process.The results demonstrate that the accuracy scores for both cases exceed 0.8.Moreover,the simple dimensionless inputs in the present model can be calculated conveniently without numerical simulations,thereby facilitating the recommendation of process parameters.
文摘In order to obtain better inverse synthetic aperture radar(ISAR)image,a novel structure-enhanced spatial spectrum is proposed for estimating the incoherence parameters and fusing multiband.The proposed method takes full advantage of the original electromagnetic scattering data and its conjugated form by combining them with the novel covariance matrices.To analyse the superiority of the modified algorithm,the mathematical expression of equivalent signal to noise ratio(SNR)is derived,which can validate our proposed algorithm theoretically.In addition,compared with the conventional matrix pencil(MP)algorithm and the conventional root-multiple signal classification(Root-MUSIC)algorithm,the proposed algorithm has better parameter estimation performance and more accurate multiband fusion results at the same SNR situations.Validity and effectiveness of the proposed algorithm is demonstrated by simulation data and real radar data.
基金supported by the National Natural Science Foundation of China(Nos.51805376 and U1709208)the Zhejiang Provincial Natural Science Foundation of China(Nos.LY20E050028 and LD21E050001)。
文摘Because the hydraulic directional valve usually works in a bad working environment and is disturbed by multi-factor noise,the traditional single sensor monitoring technology is difficult to use for an accurate diagnosis of it.Therefore,a fault diagnosis method based on multi-sensor information fusion is proposed in this paper to reduce the inaccuracy and uncertainty of traditional single sensor information diagnosis technology and to realize accurate monitoring for the location or diagnosis of early faults in such valves in noisy environments.Firstly,the statistical features of signals collected by the multi-sensor are extracted and the depth features are obtained by a convolutional neural network(CNN)to form a complete and stable multi-dimensional feature set.Secondly,to obtain a weighted multi-dimensional feature set,the multi-dimensional feature sets of similar sensors are combined,and the entropy weight method is used to weight these features to reduce the interference of insensitive features.Finally,the attention mechanism is introduced to improve the dual-channel CNN,which is used to adaptively fuse the weighted multi-dimensional feature sets of heterogeneous sensors,to flexibly select heterogeneous sensor information so as to achieve an accurate diagnosis.Experimental results show that the weighted multi-dimensional feature set obtained by the proposed method has a high fault-representation ability and low information redundancy.It can diagnose simultaneously internal wear faults of the hydraulic directional valve and electromagnetic faults of actuators that are difficult to diagnose by traditional methods.This proposed method can achieve high fault-diagnosis accuracy under severe working conditions.
基金supported by the National Natural Science Foundation of China(Project No.42171361)the Research Grants Council of the Hong Kong Special Administrative Region,China,under Project PolyU 25211819the Hong Kong Polytechnic University under Projects 1-ZE8E and 1-ZVN6.
文摘Light detection and ranging(LiDAR)has contributed immensely to forest mapping and 3D tree modelling.From the perspective of data acquisition,the integration of LiDAR data from different platforms would enrich forest information at the tree and plot levels.This research develops a general framework to integrate ground-based and UAV-LiDAR(ULS)data to better estimate tree parameters based on quantitative structure modelling(QSM).This is accomplished in three sequential steps.First,the ground-based/ULS LiDAR data were co-registered based on the local density peaks of the clustered canopy.Next,redundancy and noise were removed for the ground-based/ULS LiDAR data fusion.Finally,tree modeling and biophysical parameter retrieval were based on QSM.Experiments were performed for Backpack/Handheld/UAV-based multi-platform mobile LiDAR data of a subtropical forest,including poplar and dawn redwood species.Generally,ground-based/ULS LiDAR data fusion outperforms ground-based LiDAR with respect to tree parameter estimation compared to field data.The fusion-derived tree height,tree volume,and crown volume significantly improved by up to 9.01%,5.28%,and 18.61%,respectively,in terms of rRMSE.By contrast,the diameter at breast height(DBH)is the parameter that has the least benefits from fusion,and rRMSE remains approximately the same,because stems are already well sampled from ground data.Additionally,particularly for dense forests,the fusion-derived tree parameters were improved compared to those derived from ground-based LiDAR.Ground-based LiDAR can potentially be used to estimate tree parameters in low-stand-density forests,whereby the improvement owing to fusion is not significant.
基金Supported by National Natural Science Foundation of China(No.82070920)Major Clinical Research Projects of the Three-Year Action Plan for Promoting Clinicial Skills and Clinical Innovation in Municipal Hospitals(No.SHDC2020CR1043B-010)。
文摘·AIM:To assess the reproducibility of macular perfusion parameters in non-proliferative diabetic retinopathy(NPDR)patients measured by different examiners and two different sweep modes of optical coherence tomography angiography(OCTA).·METHODS:Ninety-eight(98 eyes)patients with NPDR were included in this study.All participates were performed three times using Cirrus OCTA with Angiography 3×3 mm^(2)and 6×6 mm^(2)sweep mode by two examiners.The macular foveal avascular zone(FAZ)and vessel density(VD)in the superficial retinal layer(SRL)were measured.The reproducibility of the measurements was evaluated with intraclass correlation coefficients(ICC)and coefficient of variation(CoV).·RESULTS:The intra-mode ICCs of Angiography 3×3 mm^(2)and 6×6 mm^(2)sweep mode were 0.957 to 0.959 and 0.964 to 0.977,respectively;and the inter-mode ICCs were 0.962 to 0.970.The intra-examiner ICCs of macular perfusion parameters were>0.950;and the inter-examiner ICCs were0.928 to 0.969.All CoVs were<1.0%.·CONCLUSION:Cirrus OCTA can measure macular perfusion parameters in NPDR patients with excellent reproducibility.The measurements of FAZ and VD in the SRL determined by Angiography 3×3 mm^(2)and 6×6 mm^(2)sweep mode are highly consistent and both sweep modes are suitable for macular perfusion parameters measurement.
文摘BACKGROUND Improving the sagittal lumbar-pelvic parameters after fusion surgery is important for improving clinical outcomes.The impact of midline lumbar fusion(MIDLF)on sagittal lumbar-pelvic alignment for the management of degenerative lumbar diseases is still unknown.AIM To analyze the effects of short-segment MIDLF and minimally invasive transforaminal lumbar interbody fusion(MIS-TLIF)on sagittal lumbar-pelvic parameters.METHODS We retrospectively analyzed 63 patients with degenerative lumbar diseases who underwent single-segment MIDLF or MIS-TLIF.The imaging data of patients were collected before surgery and at the final follow-up.The radiological sagittal parameters included the lumbar lordosis(LL),lower LL,L4 slope(L4S),L5 slope(L5S),L5 incidence(L5I),L1 axis and S1 distance(LASD),pelvic incidence(PI),pelvic tilt(PT),sacral slope(SS),and PI-LL mismatch(PI-LL).Additionally,the clinical outcomes,including lower back and leg pain visual analog scale(VAS)and Oswestry disability index(ODI)scores,were also analyzed.RESULTS In both groups,LL and Lower LL significantly increased,while L5I and LASD significantly decreased at the final follow-up compared to that recorded prior to operation(P<0.05).In the MIDLF group,L4S significantly decreased compared to that recorded prior to operation(P<0.05),while the mean SS significantly increased and the PT significantly decreased compared to that recorded prior to operation(P<0.05).In the MIS-TLIF group,SS slightly increased and the mean PT value decreased compared to that recorded prior to operation,but without a statistically significant difference(P>0.05).However,the PI-LL in both groups was significantly reduced compared to that recorded prior to operation(P<0.05).There was no significant difference in the sagittal lumbar-pelvic parameters between the two groups prior to operation and at the final follow-up(P>0.05).In addition,the change in sagittal lumbar-pelvic parameters did not differ significantly,except forΔLASD within the two groups(P>0.05).The mean lower back and leg pain VAS and ODI scores in both groups were significantly improved three months after surgery and at the final follow-up.Though the mean ODI score in the MIDLF group three months after surgery was slightly higher than that in the MIS-TLIF group,there was no significant difference between the two groups at the final follow-up.CONCLUSION Short-segment MIDLF and MIS-TLIF can equally improve sagittal lumbar parameters such as LL,Lower LL,L5I,and LASD in the treatment of lumbar degenerative diseases.However,MIDLF had a larger impact on pelvic parameters than MIS-TLIF.
基金supported by the National Natural Science Foundation of China(6153102061471383)
文摘An algorithm of highly maneuvering target tracking is proposed to solve the problem of large tracking error caused by strong maneuver. In this algorithm, a new estimator, named as multi-parameter fusion Singer (MF-Singer) model is derived based on the Singer model and the fuzzy reasoning method by using radial acceleration and velocity of the target, and applied to the problem of maneuvering target tracking in strong maneuvering environment and operating environment. The tracking performance of the MF-Singer model is evaluated and compared with other manuevering tracking models. It is shown that the MF-Singer model outperforms these algorithms in several examples.
文摘Medical image fusion has been developed as an efficient assistive technology in various clinical applications such as medical diagnosis and treatment planning.Aiming at the problem of insufficient protection of image contour and detail information by traditional image fusion methods,a new multimodal medical image fusion method is proposed.This method first uses non-subsampled shearlet transform to decompose the source image to obtain high and low frequency subband coefficients,then uses the latent low rank representation algorithm to fuse the low frequency subband coefficients,and applies the improved PAPCNN algorithm to fuse the high frequency subband coefficients.Finally,based on the automatic setting of parameters,the optimization method configuration of the time decay factorαe is carried out.The experimental results show that the proposed method solves the problems of difficult parameter setting and insufficient detail protection ability in traditional PCNN algorithm fusion images,and at the same time,it has achieved great improvement in visual quality and objective evaluation indicators.
基金funded by the National Natural Science Foundation of China,grant number 61302188.
文摘Multimodal medical image fusion can help physicians provide more accurate treatment plans for patients, as unimodal images provide limited valid information. To address the insufficient ability of traditional medical image fusion solutions to protect image details and significant information, a new multimodality medical image fusion method(NSST-PAPCNNLatLRR) is proposed in this paper. Firstly, the high and low-frequency sub-band coefficients are obtained by decomposing the source image using NSST. Then, the latent low-rank representation algorithm is used to process the low-frequency sub-band coefficients;An improved PAPCNN algorithm is also proposed for the fusion of high-frequency sub-band coefficients. The improved PAPCNN model was based on the automatic setting of the parameters, and the optimal method was configured for the time decay factor αe. The experimental results show that, in comparison with the five mainstream fusion algorithms, the new algorithm has significantly improved the visual effect over the comparison algorithm,enhanced the ability to characterize important information in images, and further improved the ability to protect the detailed information;the new algorithm has achieved at least four firsts in six objective indexes.
基金Supported by National Key R&D Program of China(Grant Nos.2020YFB1709901,2020YFB1709904)National Natural Science Foundation of China(Grant Nos.51975495,51905460)+1 种基金Guangdong Provincial Basic and Applied Basic Research Foundation of China(Grant No.2021-A1515012286)Science and Technology Plan Project of Fuzhou City of China(Grant No.2022-P-022).
文摘The accurate estimation of parameters is the premise for establishing a high-fidelity simulation model of a valve-controlled cylinder system.Bench test data are easily obtained,but it is challenging to emulate actual loads in the research on parameter estimation of valve-controlled cylinder system.Despite the actual load information contained in the operating data of the control valve,its acquisition remains challenging.This paper proposes a method that fuses bench test and operating data for parameter estimation to address the aforementioned problems.The proposed method is based on Bayesian theory,and its core is a pool fusion of prior information from bench test and operating data.Firstly,a system model is established,and the parameters in the model are analysed.Secondly,the bench and operating data of the system are collected.Then,the model parameters and weight coefficients are estimated using the data fusion method.Finally,the estimated effects of the data fusion method,Bayesian method,and particle swarm optimisation(PSO)algorithm on system model parameters are compared.The research shows that the weight coefficient represents the contribution of different prior information to the parameter estimation result.The effect of parameter estimation based on the data fusion method is better than that of the Bayesian method and the PSO algorithm.Increasing load complexity leads to a decrease in model accuracy,highlighting the crucial role of the data fusion method in parameter estimation studies.
基金supported by the Natural Science Foundation of Guangdong Province(No.2019A1515012040).
文摘As a typical laser additive manufacturing technology,laser powder bed fusion(LPBF)has achieved demonstration applications in aerospace,biomedical and other fields.However,how to select process parameters quickly and reasonably is still themain concern of LPBF production.In order to quantitatively analyze the influence of different process parameters(laser power,scanning speed,hatch space and layer thickness)on the LPBF process,the multilayer and multi-path forming process of LPBF was predicted based on the open-source discrete element method framework Yade and the open-source finite volume method framework OpenFOAM.Based on the design of experiments method,a four-factor three-level orthogonal test scheme was designed,and the porosity and surface roughness data of each calculation scheme were extracted.By analyzing the orthogonal test data,it was found that as the laser power increased,the porosity decreased,and as the scanning speed,hatch space,and layer thickness increased,the porosity increased.In addition,the influence of laser power and scanning speed on surface roughness showed a trend of decreasing first and then increasing,while the influence of scanning distance and layer thickness on surface roughness showed amonotonous increasing trend.The order of the influence of each process parameter on porosity was:scanning speed>laying thickness>laser power>hatch space,and the order of the influence of each process parameter on surface roughness was:hatch space>layer thickness>laser power>scanning speed.So the porosity of the part is most sensitive to scanning speed,and the surface roughness is the most sensitive to hatch space.The above conclusions are expected to provide process control basis for actual LPBF production of the 316L stainless steel alloy.
文摘Intelligence and perception are two operative technologies in 6G scenarios.The intelligent wireless network and information perception require a deep fusion of artificial intelligence(AI)and wireless communications in 6G systems.Therefore,fusion is becoming a typical feature and key challenge of 6G wireless communication systems.In this paper,we focus on the critical issues and propose three application scenarios in 6G wireless systems.Specifically,we first discuss the fusion of AI and 6G networks for the enhancement of 5G-advanced technology and future wireless communication systems.Then,we introduce the wireless AI technology architecture with 6G multidimensional information perception,which includes the physical layer technology of multi-dimensional feature information perception,full spectrum fusion technology,and intelligent wireless resource management.The discussion of key technologies for intelligent 6G wireless network networks is expected to provide a guideline for future research.
基金Project was supported by National Natural Science Foundation of China(Grant No.62173170).
文摘The successful confinement of the arc by the flux band depends on the welding process parameters for achieving single-pass,multi-layer, and ultra-narrow gap welding. The sidewall fusion depth, the width of the heat-affected zone, and the line energy are utilized as comprehensive indications of the quality of the welded joint. In order to achieve well fusion and reduce the heat input to the base metal.Three welding process characteristics were chosen as the primary determinants, including welding voltage, welding speed, and wire feeding speed. The metamodel of the welding quality index was built by the orthogonal experiments. The metamodel and NSGA-Ⅱ(Non-dominated sorting genetic algorithm Ⅱ) were combined to develop a multi-objective optimization model of ultra-narrow gap welding process parameters. The results showed that the optimized welding process parameters can increase the sidewall fusion depth, reduce the width of the heataffected zone and the line energy, and to some extent improve the overall quality of the ultra-narrow gap welding process.
文摘This paper starts with untime-diversification of the time-diversification deformation model and gives displacement distribution model of untime-diversification and simplifies further the study of deformation model. The paper discusses the problem of least squares fitting of coordinate parameters model—parameters of deformation model. During discussion, the basic means of cubic B splines and two steps of multidimensional disorder datum fitting are adopted which can make fitting function calculated mostly approximate coordinate parameters model and it can make calculation easier.
基金project supported by the National Natural Science Foundation of China(Grant Nos.52225503 and 52405380)National Key Research and Development Program(Grant Nos.2023YFB4603303 and 2023YFB4603304)+4 种基金Key Research and Development Program of Jiangsu Province(Grant Nos.BE2022069 and BE2022069-3)National Natural Science Foundation of China for Creative Research Groups(Grant No.51921003)The 15th Batch of“Six Talents Peaks”Innovative Talents Team Program of Jiangsu province(Grant Nos.TD-GDZB-001)Shanghai Aerospace Science and Technology Innovation Fund Project(Grant No.SAST2023-066)The Fundamental Research Funds for the Central Universities(Grant Nos.NS2023035 and NP2024128)。
文摘Transpiration cooling is crucial for the performance of aerospace engine components,relying heavily on the processing quality and accuracy of microchannels.Laser powder bed fusion(LPBF)offers the potential for integrated manufacturing of complex parts and precise microchannel fabrication,essential for engine cooling applications.However,optimizing LPBF’s extensive process parameters to control processing quality and microchannel accuracy effectively remains a significant challenge,especially given the time-consuming and labor-intensive nature of handling numerous variables and the need for thorough data analysis and correlation discovery.This study introduced a combined methodology of high-throughput experiments and Gaussian process algorithms to optimize the processing quality and accuracy of nickel-based high-temperature alloy with microchannel structures.250 parameter combinations,including laser power,scanning speed,channel diameter,and spot compensation,were designed across ten high-throughput specimens.This setup allowed for rapid and efficient evaluation of processing quality and microchannel accuracy.Employing Bayesian optimization,the Gaussian process model accurately predicted processing outcomes over a broad parameter range.The correlation between various processing parameters,processing quality and accuracy was revealed,and various optimized process combinations were summarized.Verification through computed Tomography testing of the specimens confirmed the effectiveness and precision of this approach.The approach introduced in this research provides a way for quickly and efficiently optimizing the process parameters and establishing process-property relationships for LPBF,which has broad application value.
基金Project(2022YFC2406000)supported by the National Key R&D Program,ChinaProject(2022GDASZH-2022010107)supported by the Guangdong Academy of Science,China+4 种基金Project(2019BT02C629)supported by the Guangdong Special Support Program,ChinaProject(2022GDASZH-2022010203-003)supported by the GDAS’project of Science and Technology Development,ChinaProjects(2023B1212120008,2023B1212060045)supported by the Guangdong Province Science and Technology Plan Projects,ChinaProject(2023TQ07Z559)supported by the Special Support Foundation of Guangdong Province,ChinaProject(52105293)supported by the National Natural Science Foundation of China。
文摘Laser powder-bed fusion(LPBF)of Zn-0.8Cu(wt.%)alloys exhibits significant advantages in the customization of biodegradable bone implants.However,the formability of LPBFed Zn alloy is not sufficient due to the spheroidization during the interaction of powder and laser beam,of which the mechanism is still not well understood.In this study,the evolution of morphology and grain structure of the LPBFed Zn-Cu alloy was investigated based on single-track deposition experiments.As the scanning speed increases,the grain structure of a single track of Zn-Cu alloy gradually refines,but the formability deteriorates,leading to the defect’s formation in the subsequent fabrication.The Zn-Cu alloys fabricated by optimum processing parameters exhibit a tensile strength of 157.13 MPa,yield strength of 106.48 MPa and elongation of 14.7%.This work provides a comprehensive understanding of the processing optimization of Zn-Cu alloy,achieving LPBFed Zn-Cu alloy with high density and excellent mechanical properties.
基金supported by the funding provided by Boeing Center for Aviation and Aerospace Safety.
文摘Powder bed fusion(PBF)in metallic additive manufacturing offers the ability to produce intricate geometries,high-strength components,and reliable products.However,powder processing before energy-based binding significantly impacts the final product’s integrity.Processing maps guide efficient process design to minimize defects,but creating them through experimentation alone is challenging due to the wide range of parameters,necessitating a comprehensive computational parametric analysis.In this study,we used the discrete element method to parametrically analyze the powder processing design space in PBF of stainless steel 316L powders.Uniform lattice parameter sweeps are often used for parametric analysis,but are computationally intensive.We find that non-uniform parameter sweep based on the low discrepancy sequence(LDS)algorithm is ten times more efficient at exploring the design space while accurately capturing the relationship between powder flow dynamics and bed packing density.We introduce a multi-layer perceptron(MLP)model to interpolate parametric causalities within the LDS parameter space.With over 99%accuracy,it effectively captures these causalities while requiring fewer simulations.Finally,we generate processing design maps for machine setups and powder selections for efficient process design.We find that recoating speed has the highest impact on powder processing quality,followed by recoating layer thickness,particle size,and inter-particle friction.
文摘采用激光粉末床熔融(laser powder bed fusion,LPBF)技术制备K418B高温合金,利用光学显微镜、扫描电镜和硬度仪分析工艺参数激光功率(140~220 W)和扫描速度(600~1400 mm/s)对显微缺陷、致密度、微观组织及硬度的影响。结果表明,激光功率和扫描速度均显著影响样品的相对密度与缺陷分布。低能量密度易产生不规则孔洞,高能量密度则易形成球形气孔与凝固裂纹;体积能量密度(volume energy density,VED)过低或过高都会降低致密度和性能。最佳工艺参数为激光功率180 W、扫描速度1400 mm/s,在该条件下样品致密度可达99.95%以上,表面缺陷少,仅有少量凝固裂纹,显微组织呈明显熔池边界和胞状结构,维氏硬度达366.8HV_(0.2)。微观组织观察显示,熔池边界处晶粒较粗大,内部可见细胞状柱状晶,局部连续跨越多个熔池,表现出快速凝固特征。硬度随VED先升后降,与孔隙含量及致密度变化一致。研究揭示热应力是裂纹产生的主要原因,为K418B合金LPBF成形的参数优化提供依据,对提升航空发动机关键部件制造质量具有工程应用价值。
基金supported financially by the National Natural Science Foundation of China(T2121003 received by X.D.,and U23A20638 received by Y.J.)the National Key Research and Development Program of China(2023YFB3208000 and 2023YFB3208001 received by Y.J.).
文摘Flexible sensing array integrated with multiple sensors is an attractive approach for flight parameter detection.However,the poor resolution of flexible sensors and time-consuming neural network processes mitigate their accuracy and adaptability in predicting flight parameters.Here we present an ultra-thin flexible sensing patch with a new configuration,comprising a differential pressure sensor array and a vector flow velocity sensor.The capacitive differential pressure sensor array is fabricated by a multilayer polyimide bonding technique,reaching a resolution of 0.14 Pa.To solve flight parameters with the flexible sensing patch,we develop an analytical pressure-velocity fusion algorithm,enabling fast response and high accuracy in flight parameter detection.The average errors in calculating the angle of attack,angle of sideslip,and airspeed are 0.22°,0.35°,and 0.73 m s^(-1),respectively.The high-resolution flexible sensors and novel analytical pressure-velocity fusion algorithm pave the way for flexible sensing patch-based air data sensing techniques.
