There are multiple operating modes in the real industrial process, and the collected data follow the complex multimodal distribution, so most traditional process monitoring methods are no longer applicable because the...There are multiple operating modes in the real industrial process, and the collected data follow the complex multimodal distribution, so most traditional process monitoring methods are no longer applicable because their presumptions are that sampled-data should obey the single Gaussian distribution or non-Gaussian distribution. In order to solve these problems, a novel weighted local standardization(WLS) strategy is proposed to standardize the multimodal data, which can eliminate the multi-mode characteristics of the collected data, and normalize them into unimodal data distribution. After detailed analysis of the raised data preprocessing strategy, a new algorithm using WLS strategy with support vector data description(SVDD) is put forward to apply for multi-mode monitoring process. Unlike the strategy of building multiple local models, the developed method only contains a model without the prior knowledge of multi-mode process. To demonstrate the proposed method's validity, it is applied to a numerical example and a Tennessee Eastman(TE) process. Finally, the simulation results show that the WLS strategy is very effective to standardize multimodal data, and the WLS-SVDD monitoring method has great advantages over the traditional SVDD and PCA combined with a local standardization strategy(LNS-PCA) in multi-mode process monitoring.展开更多
A new modeling and monitoring approach for multi-mode processes is proposed.The method of similarity measure(SM) and kernel principal component analysis(KPCA) are integrated to construct SM-KPCA monitoring scheme,wher...A new modeling and monitoring approach for multi-mode processes is proposed.The method of similarity measure(SM) and kernel principal component analysis(KPCA) are integrated to construct SM-KPCA monitoring scheme,where SM method serves as the separation of common subspace and specific subspace.Compared with the traditional methods,the main contributions of this work are:1) SM consisted of two measures of distance and angle to accommodate process characters.The different monitoring effect involves putting on the different weight,which would simplify the monitoring model structure and enhance its reliability and robustness.2) The proposed method can be used to find faults by the common space and judge which mode the fault belongs to by the specific subspace.Results of algorithm analysis and fault detection experiments indicate the validity and practicability of the presented method.展开更多
The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can caus...The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods.展开更多
Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim ...Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim ...Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim ...Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim ...Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
[Objective]Accurate prediction of tomato growth height is crucial for optimizing production environments in smart farming.However,current prediction methods predominantly rely on empirical,mechanistic,or learning-base...[Objective]Accurate prediction of tomato growth height is crucial for optimizing production environments in smart farming.However,current prediction methods predominantly rely on empirical,mechanistic,or learning-based models that utilize either images data or environmental data.These methods fail to fully leverage multi-modal data to capture the diverse aspects of plant growth comprehensively.[Methods]To address this limitation,a two-stage phenotypic feature extraction(PFE)model based on deep learning algorithm of recurrent neural network(RNN)and long short-term memory(LSTM)was developed.The model integrated environment and plant information to provide a holistic understanding of the growth process,emploied phenotypic and temporal feature extractors to comprehensively capture both types of features,enabled a deeper understanding of the interaction between tomato plants and their environment,ultimately leading to highly accurate predictions of growth height.[Results and Discussions]The experimental results showed the model's ef‐fectiveness:When predicting the next two days based on the past five days,the PFE-based RNN and LSTM models achieved mean absolute percentage error(MAPE)of 0.81%and 0.40%,respectively,which were significantly lower than the 8.00%MAPE of the large language model(LLM)and 6.72%MAPE of the Transformer-based model.In longer-term predictions,the 10-day prediction for 4 days ahead and the 30-day prediction for 12 days ahead,the PFE-RNN model continued to outperform the other two baseline models,with MAPE of 2.66%and 14.05%,respectively.[Conclusions]The proposed method,which leverages phenotypic-temporal collaboration,shows great potential for intelligent,data-driven management of tomato cultivation,making it a promising approach for enhancing the efficiency and precision of smart tomato planting management.展开更多
Applying bio-oxidation waste solution(BOS)to chemical-biological two-stage oxidation process can significantly improve the bio-oxidation efficiency of arsenopyrite.This study aims to clarify the enhanced oxidation mec...Applying bio-oxidation waste solution(BOS)to chemical-biological two-stage oxidation process can significantly improve the bio-oxidation efficiency of arsenopyrite.This study aims to clarify the enhanced oxidation mechanism of arsenopyrite by evaluating the effects of physical and chemical changes of arsenopyrite in BOS chemical oxidation stage on mineral dissolution kinetics,as well as microbial growth activity and community structure composition in bio-oxidation stage.The results showed that the chemical oxidation contributed to destroying the physical and chemical structure of arsenopyrite surface and reducing the particle size,and led to the formation of nitrogenous substances on mineral surface.These chemical oxidation behaviors effectively promoted Fe^(3+)cycling in the bio-oxidation system and weakened the inhibitory effect of the sulfur film on ionic diffusion,thereby enhancing the dissolution kinetics of the arsenopyrite.Therefore,the bio-oxidation efficiency of arsenopyrite was significantly increased in the two-stage oxidation process.After 18 d,the two-stage oxidation process achieved total extraction rates of(88.8±2.0)%,(86.7±1.3)%,and(74.7±3.0)%for As,Fe,and S elements,respectively.These values represented a significant increase of(50.8±3.4)%,(47.1±2.7)%,and(46.0±0.7)%,respectively,compared to the one-stage bio-oxidation process.展开更多
By combining with an improved model on engraving process,a two-phase flow interior ballistic model has been proposed to accurately predict the flow and energy conversion behaviors of pyrotechnic actuators.Using comput...By combining with an improved model on engraving process,a two-phase flow interior ballistic model has been proposed to accurately predict the flow and energy conversion behaviors of pyrotechnic actuators.Using computational fluid dynamics(CFD),the two-phase flow and piston engraving characteristics of a pyrotechnic actuator are investigated.Initially,the current model was utilized to examine the intricate,multi-dimensional flow,and energy conversion characteristics of the propellant grains and combustion gas within the pyrotechnic actuator chamber.It was discovered that the combustion gas on the wall's constant transition from potential to kinetic energy,along with the combined effect of the propellant motion,are what create the pressure oscillation within the chamber.Additionally,a numerical analysis was conducted to determine the impact of various parameters on the pressure oscillation and piston motion,including pyrotechnic charge,pyrotechnic particle size,and chamber structural dimension.The findings show that decreasing the pyrotechnic charge will lower the terminal velocity,while increasing and decreasing the pyrotechnic particle size will reduce the pressure oscillation in the chamber.The pyrotechnic particle size has minimal bearing on the terminal velocity.The results of this investigation offer a trustworthy forecasting instrument for comprehending and creating pyrotechnic actuator designs.展开更多
Breakage is an important step in the resource processing chain.However,the mechanical crushing methods commonly used today suffer from low energy efficiency and high dust levels.Promoting environmental protection and ...Breakage is an important step in the resource processing chain.However,the mechanical crushing methods commonly used today suffer from low energy efficiency and high dust levels.Promoting environmental protection and improving energy efficiency are crucial to advancing China’s circular economy.Mining companies are actively exploring novel and innovative technologies to significantly cut down on operating costs and minimize emissions of dust and pollutants generated during processing.Recently,high voltage pulse discharge(HVPD)technology has received widespread attention and has been reported to have good application prospects in resource processing.This paper presents an extensive review of the operational principles of HVPD and the unique characteristics it engenders,such as non-polluting,selective material fragmentation,pre-weakening,pre-concentration,and enhanced permeability of coal seams.Additionally,this review explores the potential and obstacles confronting HVPD in industrial contexts,offering fresh insights for HVPD optimization and providing guidance and prospects for industrial deployment and further development.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
This study focused on the production of polypropylene(PP)/silver(Ag)composites via additive manufacturing.This study aimed to enhance the quality of medical-grade PP in material extrusion(MEX)three-dimensional printin...This study focused on the production of polypropylene(PP)/silver(Ag)composites via additive manufacturing.This study aimed to enhance the quality of medical-grade PP in material extrusion(MEX)three-dimensional printing(3DP)by improving its mechanical properties while simultaneously adding antibacterial properties.The latter can find extremely important and versatile properties that are applicable in defense and security domains.PP/Ag nanocomposites were prepared using a novel method based on a reaction occurring while mixing appropriate quantities of the starting polymers and additives,namely polyvinylpyrrolidone(PVP)as the matrix material and silver nitrate(AgNO_(3))as the filler.This process produced three-dimensional(3D)printed filaments,which were then used to create specimens for a series of standardized tests.It was found that the mechanical properties of the nanocomposites were enhanced in relation to pristine PP,especially for the PP matrix with various loadings of AgNO_(3)and PVP,such as 5.0 wt%and 2.5 wt%,respectively.The voids,inclusions,and actual-to-nominal dimensions also showed improved results.The 3DP specimens exhibited a more effective biocidal performance against Staphylococcus aureus than Escherichia coli,which developed an inhibition zone only in the case of PP with filler loading percentages of AgNO_(3)and PVP at 10.0 wt%and 5.0 wt%,respectively Compounds possessing such properties can be beneficial for various applications requiring increased mechanical properties and biocidal capabilities,such as in the Defence or medical industries.展开更多
For the multi-mode radar working in the modern electronicbattlefield, different working states of one single radar areprone to being classified as multiple emitters when adoptingtraditional classification methods to p...For the multi-mode radar working in the modern electronicbattlefield, different working states of one single radar areprone to being classified as multiple emitters when adoptingtraditional classification methods to process intercepted signals,which has a negative effect on signal classification. A classificationmethod based on spatial data mining is presented to address theabove challenge. Inspired by the idea of spatial data mining, theclassification method applies nuclear field to depicting the distributioninformation of pulse samples in feature space, and digs out thehidden cluster information by analyzing distribution characteristics.In addition, a membership-degree criterion to quantify the correlationamong all classes is established, which ensures classificationaccuracy of signal samples. Numerical experiments show that thepresented method can effectively prevent different working statesof multi-mode emitter from being classified as several emitters,and achieve higher classification accuracy.展开更多
The classic multi-mode input shapers(MMISs)are valid to decrease multi-mode residual vibration of manipulators or robots simultaneously.But these input shapers cannot suppress more residual vibration with a quick resp...The classic multi-mode input shapers(MMISs)are valid to decrease multi-mode residual vibration of manipulators or robots simultaneously.But these input shapers cannot suppress more residual vibration with a quick response time when the frequency bandwidth of each mode vibration is very different.The methodologies and various types of multi-mode classic and hybrid input shaping control schemes with positive impulses were introduced in this paper.Six types of two-mode hybrid input shapers with positive impulses of a 3 degree of freedom robot were established.The ability and robustness of these two-mode hybrid input shapers to suppress residual vibration were analyzed by vibration response curve and sensitivity curve via numerical simulation.The response time of the zero vibration-zero vibration and derivative(ZV-ZVD)input shaper is the fastest,but the robustness is the least.The robustness of the zero vibration and derivative-extra insensitive(ZVD-EI)input shaper is the best,while the response time is the longest.According to the frequency bandwidth at each mode and required system response time,the most appropriate multi-mode hybrid input shaper(MMHIS)can be selected in order to improve response time as much as possible under the condition of suppressing more residual vibration.展开更多
A memetic algorithm （MA） for a multi-mode resourceconstrained project scheduling problem （MRCPSP） is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The f...A memetic algorithm （MA） for a multi-mode resourceconstrained project scheduling problem （MRCPSP） is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The fitness function makes use of a mechanism called ＂strategic oscillation＂ to make the search process have a higher probability to visit solutions around a ＂feasible boundary＂. One of the local search procedures aims at improving the lower bound of project makespan to be less than a known upper bound, and another aims at improving a solution of an MRCPSP instance accepting infeasible solutions based on the new fitness function in the search process. A detailed computational experiment is set up using instances from the problem instance library PSPLIB. Computational results show that the proposed MA is very competitive with the state-of-the-art algorithms. The MA obtains improved solutions for one instance of set J30.展开更多
The launch dynamics theory for multibody systems emerges as an innovative and efficacious approach for the study of launch dynamics,capable of addressing the challenges of complex modeling,diminished computational eff...The launch dynamics theory for multibody systems emerges as an innovative and efficacious approach for the study of launch dynamics,capable of addressing the challenges of complex modeling,diminished computational efficiency,and imprecise analyses of system dynamic responses found in the dynamics research of intricate multi-rigid-flexible body systems,such as self-propelled artillery.This advancement aims to enhance the firing accuracy and launch safety of self-propelled artillery.Recognizing the shortfall of overlooking the band engraving process in existing theories,this study introduces a novel coupling calculation methodology for the launch dynamics of a self-propelled artillery multibody system.This method leverages the ABAQUS subroutine interface VUAMP to compute the dynamic response of the projectile and barrel during the launch process of large-caliber self-propelled artillery.Additionally,it examines the changes in projectile resistance and band deformation in relation to projectile motion throughout the band engraving process.Comparative analysis of the computational outcomes with experimental data evidences that the proposed method offers a more precise depiction of the launch process of self-propelled artillery,thereby enhancing the accuracy of launch dynamics calculations for self-propelled artillery.展开更多
A novel method for noise removal from the rotating accelerometer gravity gradiometer(MAGG)is presented.It introduces a head-to-tail data expansion technique based on the zero-phase filtering principle.A scheme for det...A novel method for noise removal from the rotating accelerometer gravity gradiometer(MAGG)is presented.It introduces a head-to-tail data expansion technique based on the zero-phase filtering principle.A scheme for determining band-pass filter parameters based on signal-to-noise ratio gain,smoothness index,and cross-correlation coefficient is designed using the Chebyshev optimal consistent approximation theory.Additionally,a wavelet denoising evaluation function is constructed,with the dmey wavelet basis function identified as most effective for processing gravity gradient data.The results of hard-in-the-loop simulation and prototype experiments show that the proposed processing method has shown a 14%improvement in the measurement variance of gravity gradient signals,and the measurement accuracy has reached within 4E,compared to other commonly used methods,which verifies that the proposed method effectively removes noise from the gradient signals,improved gravity gradiometry accuracy,and has certain technical insights for high-precision airborne gravity gradiometry.展开更多
Mill vibration is a common problem in rolling production,which directly affects the thickness accuracy of the strip and may even lead to strip fracture accidents in serious cases.The existing vibration prediction mode...Mill vibration is a common problem in rolling production,which directly affects the thickness accuracy of the strip and may even lead to strip fracture accidents in serious cases.The existing vibration prediction models do not consider the features contained in the data,resulting in limited improvement of model accuracy.To address these challenges,this paper proposes a multi-dimensional multi-modal cold rolling vibration time series prediction model(MDMMVPM)based on the deep fusion of multi-level networks.In the model,the long-term and short-term modal features of multi-dimensional data are considered,and the appropriate prediction algorithms are selected for different data features.Based on the established prediction model,the effects of tension and rolling force on mill vibration are analyzed.Taking the 5th stand of a cold mill in a steel mill as the research object,the innovative model is applied to predict the mill vibration for the first time.The experimental results show that the correlation coefficient(R^(2))of the model proposed in this paper is 92.5%,and the root-mean-square error(RMSE)is 0.0011,which significantly improves the modeling accuracy compared with the existing models.The proposed model is also suitable for the hot rolling process,which provides a new method for the prediction of strip rolling vibration.展开更多
Intelligent personal assistants play a pivotal role in in-vehicle systems,significantly enhancing life efficiency,driving safety,and decision-making support.In this study,the multi-modal design elements of intelligent...Intelligent personal assistants play a pivotal role in in-vehicle systems,significantly enhancing life efficiency,driving safety,and decision-making support.In this study,the multi-modal design elements of intelligent personal assistants within the context of visual,auditory,and somatosensory interactions with drivers were discussed.Their impact on the driver’s psychological state through various modes such as visual imagery,voice interaction,and gesture interaction were explored.The study also introduced innovative designs for in-vehicle intelligent personal assistants,incorporating design principles such as driver-centricity,prioritizing passenger safety,and utilizing timely feedback as a criterion.Additionally,the study employed design methods like driver behavior research and driving situation analysis to enhance the emotional connection between drivers and their vehicles,ultimately improving driver satisfaction and trust.展开更多
基金Project(61374140)supported by the National Natural Science Foundation of China
文摘There are multiple operating modes in the real industrial process, and the collected data follow the complex multimodal distribution, so most traditional process monitoring methods are no longer applicable because their presumptions are that sampled-data should obey the single Gaussian distribution or non-Gaussian distribution. In order to solve these problems, a novel weighted local standardization(WLS) strategy is proposed to standardize the multimodal data, which can eliminate the multi-mode characteristics of the collected data, and normalize them into unimodal data distribution. After detailed analysis of the raised data preprocessing strategy, a new algorithm using WLS strategy with support vector data description(SVDD) is put forward to apply for multi-mode monitoring process. Unlike the strategy of building multiple local models, the developed method only contains a model without the prior knowledge of multi-mode process. To demonstrate the proposed method's validity, it is applied to a numerical example and a Tennessee Eastman(TE) process. Finally, the simulation results show that the WLS strategy is very effective to standardize multimodal data, and the WLS-SVDD monitoring method has great advantages over the traditional SVDD and PCA combined with a local standardization strategy(LNS-PCA) in multi-mode process monitoring.
基金Projects(61273163,61325015,61304121)supported by the National Natural Science Foundation of China
文摘A new modeling and monitoring approach for multi-mode processes is proposed.The method of similarity measure(SM) and kernel principal component analysis(KPCA) are integrated to construct SM-KPCA monitoring scheme,where SM method serves as the separation of common subspace and specific subspace.Compared with the traditional methods,the main contributions of this work are:1) SM consisted of two measures of distance and angle to accommodate process characters.The different monitoring effect involves putting on the different weight,which would simplify the monitoring model structure and enhance its reliability and robustness.2) The proposed method can be used to find faults by the common space and judge which mode the fault belongs to by the specific subspace.Results of algorithm analysis and fault detection experiments indicate the validity and practicability of the presented method.
基金Projects(U22B2084,52275483,52075142)supported by the National Natural Science Foundation of ChinaProject(2023ZY01050)supported by the Ministry of Industry and Information Technology High Quality Development,China。
文摘The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods.
文摘Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
文摘Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
文摘Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
文摘Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
文摘[Objective]Accurate prediction of tomato growth height is crucial for optimizing production environments in smart farming.However,current prediction methods predominantly rely on empirical,mechanistic,or learning-based models that utilize either images data or environmental data.These methods fail to fully leverage multi-modal data to capture the diverse aspects of plant growth comprehensively.[Methods]To address this limitation,a two-stage phenotypic feature extraction(PFE)model based on deep learning algorithm of recurrent neural network(RNN)and long short-term memory(LSTM)was developed.The model integrated environment and plant information to provide a holistic understanding of the growth process,emploied phenotypic and temporal feature extractors to comprehensively capture both types of features,enabled a deeper understanding of the interaction between tomato plants and their environment,ultimately leading to highly accurate predictions of growth height.[Results and Discussions]The experimental results showed the model's ef‐fectiveness:When predicting the next two days based on the past five days,the PFE-based RNN and LSTM models achieved mean absolute percentage error(MAPE)of 0.81%and 0.40%,respectively,which were significantly lower than the 8.00%MAPE of the large language model(LLM)and 6.72%MAPE of the Transformer-based model.In longer-term predictions,the 10-day prediction for 4 days ahead and the 30-day prediction for 12 days ahead,the PFE-RNN model continued to outperform the other two baseline models,with MAPE of 2.66%and 14.05%,respectively.[Conclusions]The proposed method,which leverages phenotypic-temporal collaboration,shows great potential for intelligent,data-driven management of tomato cultivation,making it a promising approach for enhancing the efficiency and precision of smart tomato planting management.
基金Project(52274348)supported by the National Natural Science Foundation of ChinaProject(2022JH1/10400024)supported by the Major Projects for the“Revealed Top”Science and Technology of Liaoning Province,China。
文摘Applying bio-oxidation waste solution(BOS)to chemical-biological two-stage oxidation process can significantly improve the bio-oxidation efficiency of arsenopyrite.This study aims to clarify the enhanced oxidation mechanism of arsenopyrite by evaluating the effects of physical and chemical changes of arsenopyrite in BOS chemical oxidation stage on mineral dissolution kinetics,as well as microbial growth activity and community structure composition in bio-oxidation stage.The results showed that the chemical oxidation contributed to destroying the physical and chemical structure of arsenopyrite surface and reducing the particle size,and led to the formation of nitrogenous substances on mineral surface.These chemical oxidation behaviors effectively promoted Fe^(3+)cycling in the bio-oxidation system and weakened the inhibitory effect of the sulfur film on ionic diffusion,thereby enhancing the dissolution kinetics of the arsenopyrite.Therefore,the bio-oxidation efficiency of arsenopyrite was significantly increased in the two-stage oxidation process.After 18 d,the two-stage oxidation process achieved total extraction rates of(88.8±2.0)%,(86.7±1.3)%,and(74.7±3.0)%for As,Fe,and S elements,respectively.These values represented a significant increase of(50.8±3.4)%,(47.1±2.7)%,and(46.0±0.7)%,respectively,compared to the one-stage bio-oxidation process.
基金supported by the National Natural Science Foundation of China(Grant No.11972194).
文摘By combining with an improved model on engraving process,a two-phase flow interior ballistic model has been proposed to accurately predict the flow and energy conversion behaviors of pyrotechnic actuators.Using computational fluid dynamics(CFD),the two-phase flow and piston engraving characteristics of a pyrotechnic actuator are investigated.Initially,the current model was utilized to examine the intricate,multi-dimensional flow,and energy conversion characteristics of the propellant grains and combustion gas within the pyrotechnic actuator chamber.It was discovered that the combustion gas on the wall's constant transition from potential to kinetic energy,along with the combined effect of the propellant motion,are what create the pressure oscillation within the chamber.Additionally,a numerical analysis was conducted to determine the impact of various parameters on the pressure oscillation and piston motion,including pyrotechnic charge,pyrotechnic particle size,and chamber structural dimension.The findings show that decreasing the pyrotechnic charge will lower the terminal velocity,while increasing and decreasing the pyrotechnic particle size will reduce the pressure oscillation in the chamber.The pyrotechnic particle size has minimal bearing on the terminal velocity.The results of this investigation offer a trustworthy forecasting instrument for comprehending and creating pyrotechnic actuator designs.
基金Foundation item:Project(2023YFC2909000) supported by the National Key R&D Program for Young Scientists,ChinaProject(2023JH3/10200010) supported by the Excellent Youth Natural Science Foundation of Liaoning Province,China+3 种基金Project (XLYC2203167) supported by the Liaoning Revitalization Talents Program,ChinaProject(RC231175) supported by the Mid-career and Young Scientific and Technological Talents Program of Shenyang,ChinaProject(2023A03003-2) supported by the Key Special Program of Xinjiang,ChinaProject(N2301026) supported by the Fundamental Research Funds for the Central Universities,China。
文摘Breakage is an important step in the resource processing chain.However,the mechanical crushing methods commonly used today suffer from low energy efficiency and high dust levels.Promoting environmental protection and improving energy efficiency are crucial to advancing China’s circular economy.Mining companies are actively exploring novel and innovative technologies to significantly cut down on operating costs and minimize emissions of dust and pollutants generated during processing.Recently,high voltage pulse discharge(HVPD)technology has received widespread attention and has been reported to have good application prospects in resource processing.This paper presents an extensive review of the operational principles of HVPD and the unique characteristics it engenders,such as non-polluting,selective material fragmentation,pre-weakening,pre-concentration,and enhanced permeability of coal seams.Additionally,this review explores the potential and obstacles confronting HVPD in industrial contexts,offering fresh insights for HVPD optimization and providing guidance and prospects for industrial deployment and further development.
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.
文摘This study focused on the production of polypropylene(PP)/silver(Ag)composites via additive manufacturing.This study aimed to enhance the quality of medical-grade PP in material extrusion(MEX)three-dimensional printing(3DP)by improving its mechanical properties while simultaneously adding antibacterial properties.The latter can find extremely important and versatile properties that are applicable in defense and security domains.PP/Ag nanocomposites were prepared using a novel method based on a reaction occurring while mixing appropriate quantities of the starting polymers and additives,namely polyvinylpyrrolidone(PVP)as the matrix material and silver nitrate(AgNO_(3))as the filler.This process produced three-dimensional(3D)printed filaments,which were then used to create specimens for a series of standardized tests.It was found that the mechanical properties of the nanocomposites were enhanced in relation to pristine PP,especially for the PP matrix with various loadings of AgNO_(3)and PVP,such as 5.0 wt%and 2.5 wt%,respectively.The voids,inclusions,and actual-to-nominal dimensions also showed improved results.The 3DP specimens exhibited a more effective biocidal performance against Staphylococcus aureus than Escherichia coli,which developed an inhibition zone only in the case of PP with filler loading percentages of AgNO_(3)and PVP at 10.0 wt%and 5.0 wt%,respectively Compounds possessing such properties can be beneficial for various applications requiring increased mechanical properties and biocidal capabilities,such as in the Defence or medical industries.
基金supported by the National Natural Science Foundation of China(61371172)the International S&T Cooperation Program of China(2015DFR10220)+1 种基金the Ocean Engineering Project of National Key Laboratory Foundation(1213)the Fundamental Research Funds for the Central Universities(HEUCF1608)
文摘For the multi-mode radar working in the modern electronicbattlefield, different working states of one single radar areprone to being classified as multiple emitters when adoptingtraditional classification methods to process intercepted signals,which has a negative effect on signal classification. A classificationmethod based on spatial data mining is presented to address theabove challenge. Inspired by the idea of spatial data mining, theclassification method applies nuclear field to depicting the distributioninformation of pulse samples in feature space, and digs out thehidden cluster information by analyzing distribution characteristics.In addition, a membership-degree criterion to quantify the correlationamong all classes is established, which ensures classificationaccuracy of signal samples. Numerical experiments show that thepresented method can effectively prevent different working statesof multi-mode emitter from being classified as several emitters,and achieve higher classification accuracy.
基金Project(LQ12E05008)supported by Natural Science Foundation of Zhejiang Province,ChinaProject(201708330107)supported by China Scholarship Council
文摘The classic multi-mode input shapers(MMISs)are valid to decrease multi-mode residual vibration of manipulators or robots simultaneously.But these input shapers cannot suppress more residual vibration with a quick response time when the frequency bandwidth of each mode vibration is very different.The methodologies and various types of multi-mode classic and hybrid input shaping control schemes with positive impulses were introduced in this paper.Six types of two-mode hybrid input shapers with positive impulses of a 3 degree of freedom robot were established.The ability and robustness of these two-mode hybrid input shapers to suppress residual vibration were analyzed by vibration response curve and sensitivity curve via numerical simulation.The response time of the zero vibration-zero vibration and derivative(ZV-ZVD)input shaper is the fastest,but the robustness is the least.The robustness of the zero vibration and derivative-extra insensitive(ZVD-EI)input shaper is the best,while the response time is the longest.According to the frequency bandwidth at each mode and required system response time,the most appropriate multi-mode hybrid input shaper(MMHIS)can be selected in order to improve response time as much as possible under the condition of suppressing more residual vibration.
基金supported by the National Natural Science Foundation of China(71171038)
文摘A memetic algorithm （MA） for a multi-mode resourceconstrained project scheduling problem （MRCPSP） is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The fitness function makes use of a mechanism called ＂strategic oscillation＂ to make the search process have a higher probability to visit solutions around a ＂feasible boundary＂. One of the local search procedures aims at improving the lower bound of project makespan to be less than a known upper bound, and another aims at improving a solution of an MRCPSP instance accepting infeasible solutions based on the new fitness function in the search process. A detailed computational experiment is set up using instances from the problem instance library PSPLIB. Computational results show that the proposed MA is very competitive with the state-of-the-art algorithms. The MA obtains improved solutions for one instance of set J30.
基金supported by the National Natural Science Foundation of China (Grant Number:12372093)。
文摘The launch dynamics theory for multibody systems emerges as an innovative and efficacious approach for the study of launch dynamics,capable of addressing the challenges of complex modeling,diminished computational efficiency,and imprecise analyses of system dynamic responses found in the dynamics research of intricate multi-rigid-flexible body systems,such as self-propelled artillery.This advancement aims to enhance the firing accuracy and launch safety of self-propelled artillery.Recognizing the shortfall of overlooking the band engraving process in existing theories,this study introduces a novel coupling calculation methodology for the launch dynamics of a self-propelled artillery multibody system.This method leverages the ABAQUS subroutine interface VUAMP to compute the dynamic response of the projectile and barrel during the launch process of large-caliber self-propelled artillery.Additionally,it examines the changes in projectile resistance and band deformation in relation to projectile motion throughout the band engraving process.Comparative analysis of the computational outcomes with experimental data evidences that the proposed method offers a more precise depiction of the launch process of self-propelled artillery,thereby enhancing the accuracy of launch dynamics calculations for self-propelled artillery.
文摘A novel method for noise removal from the rotating accelerometer gravity gradiometer(MAGG)is presented.It introduces a head-to-tail data expansion technique based on the zero-phase filtering principle.A scheme for determining band-pass filter parameters based on signal-to-noise ratio gain,smoothness index,and cross-correlation coefficient is designed using the Chebyshev optimal consistent approximation theory.Additionally,a wavelet denoising evaluation function is constructed,with the dmey wavelet basis function identified as most effective for processing gravity gradient data.The results of hard-in-the-loop simulation and prototype experiments show that the proposed processing method has shown a 14%improvement in the measurement variance of gravity gradient signals,and the measurement accuracy has reached within 4E,compared to other commonly used methods,which verifies that the proposed method effectively removes noise from the gradient signals,improved gravity gradiometry accuracy,and has certain technical insights for high-precision airborne gravity gradiometry.
基金Project(2023JH26-10100002)supported by the Liaoning Science and Technology Major Project,ChinaProjects(U21A20117,52074085)supported by the National Natural Science Foundation of China+1 种基金Project(2022JH2/101300008)supported by the Liaoning Applied Basic Research Program Project,ChinaProject(22567612H)supported by the Hebei Provincial Key Laboratory Performance Subsidy Project,China。
文摘Mill vibration is a common problem in rolling production,which directly affects the thickness accuracy of the strip and may even lead to strip fracture accidents in serious cases.The existing vibration prediction models do not consider the features contained in the data,resulting in limited improvement of model accuracy.To address these challenges,this paper proposes a multi-dimensional multi-modal cold rolling vibration time series prediction model(MDMMVPM)based on the deep fusion of multi-level networks.In the model,the long-term and short-term modal features of multi-dimensional data are considered,and the appropriate prediction algorithms are selected for different data features.Based on the established prediction model,the effects of tension and rolling force on mill vibration are analyzed.Taking the 5th stand of a cold mill in a steel mill as the research object,the innovative model is applied to predict the mill vibration for the first time.The experimental results show that the correlation coefficient(R^(2))of the model proposed in this paper is 92.5%,and the root-mean-square error(RMSE)is 0.0011,which significantly improves the modeling accuracy compared with the existing models.The proposed model is also suitable for the hot rolling process,which provides a new method for the prediction of strip rolling vibration.
文摘Intelligent personal assistants play a pivotal role in in-vehicle systems,significantly enhancing life efficiency,driving safety,and decision-making support.In this study,the multi-modal design elements of intelligent personal assistants within the context of visual,auditory,and somatosensory interactions with drivers were discussed.Their impact on the driver’s psychological state through various modes such as visual imagery,voice interaction,and gesture interaction were explored.The study also introduced innovative designs for in-vehicle intelligent personal assistants,incorporating design principles such as driver-centricity,prioritizing passenger safety,and utilizing timely feedback as a criterion.Additionally,the study employed design methods like driver behavior research and driving situation analysis to enhance the emotional connection between drivers and their vehicles,ultimately improving driver satisfaction and trust.
