With the emergence of the concept of low-altitude economy and the continuous upgrading of avionics technology,cultivating aerospace professionals with single-chip microcomputer(SCM)knowledge and practical abilities ha...With the emergence of the concept of low-altitude economy and the continuous upgrading of avionics technology,cultivating aerospace professionals with single-chip microcomputer(SCM)knowledge and practical abilities has become an important reform direction for undergraduate education.From the perspective of course application,this paper explores the necessity of introducing SCM courses and reforming teaching methods for aerospace majors at the undergraduate level,and puts forward reform suggestions in teaching content,teaching methods,practical links,and evaluation systems.It aims to build a curriculum system that not only conforms to the characteristics of aerospace majors but also strengthens students’SCM engineering application literacy and cultivates applied compound talents for the aviation industry related to the low-altitude economy.展开更多
With the gradual penetration of artificial intelligence technology into the field of education,to explore the application value of Generative Artificial Intelligence(AIGC)in traditional teaching,this paper sorts out t...With the gradual penetration of artificial intelligence technology into the field of education,to explore the application value of Generative Artificial Intelligence(AIGC)in traditional teaching,this paper sorts out the innovative application models of AIGC with the single-chip microcomputer course as the research object.By comparing and analyzing the teaching achievements of this course in the two academic years of 2024-2025,the effectiveness of AI empowerment in improving the teaching quality of single-chip microcomputers is verified.Meanwhile,based on the Back Propagation neural network algorithm,a prediction model for students’final exam scores is constructed by integrating multidimensional data such as students’classroom performance,experimental report scores,and phased test results.After training and verification,the prediction accuracy of the model on the test set reaches 76.9%.展开更多
In recent years,research on industrial innovation and development has primarily focused on industrial automation and intelligent manufacturing.Within the field of integrating mechatronics and intelligent control,analy...In recent years,research on industrial innovation and development has primarily focused on industrial automation and intelligent manufacturing.Within the field of integrating mechatronics and intelligent control,analyzing the efficient control of mechatronic systems enabled by generative AI for single-chip microcomputers can further highlight the value and significance of promoting AI technology applications.This paper examines the technical characteristics of generative AI in data generation,multimodal fusion,and dynamic adaptation,proposing lightweight model deployment strategies that compress large generative models to a range compatible with single-chip microcomputers,ensuring local real-time inference capabilities.It constructs an edge intelligent control architecture,enabling generative AI to directly participate in decision-making instruction generation,forming a new working system of perception,decision-making,and execution.Additionally,it designs a collaborative optimization training mechanism that leverages federated learning to overcome single-machine data limitations and enhance model generalization performance.At the application level,an intelligent fault prediction system is developed for early identification of equipment anomalies,an adaptive parameter optimization module is constructed for dynamically adjusting control strategies,and a multi-device collaborative scheduling engine is established to optimize production processes,providing technical support for embedded intelligent control in Industry 4.0 scenarios.展开更多
In recent years,the application of various advanced technologies,such as digitization and informatization,has become the primary tool for innovation in education and teaching.For traditional single-chip microcomputer ...In recent years,the application of various advanced technologies,such as digitization and informatization,has become the primary tool for innovation in education and teaching.For traditional single-chip microcomputer course teaching,it is necessary to emphasize the introduction and application of high-tech innovations in its path of innovative development.This course is a typical representative of multidisciplinary teaching,involving multiple disciplines such as electronic engineering,automation,and computer science.In response to issues faced in traditional teaching,such as rigid organization of teaching content that struggles to keep pace with technological advancements,resulting in a noticeable lag in knowledge transfer,and monotonous teaching methods that fail to precisely meet the diverse learning needs of students,analyzing the innovative applications of this course under the empowerment of AI technology holds significant practical relevance.In this regard,the study relies on AI technology empowerment to analyze the application paths for the deep integration of AI technology and single-chip microcomputer courses,constructing a new teaching model to provide references for enhancing teaching quality and stimulating students’innovative potential.展开更多
This study investigates the influence of the elastic modulus(E)of the composite strata on the trough width coefficient(i).It is hypothesized that,in composite strata,the relationship between the trough width coefficie...This study investigates the influence of the elastic modulus(E)of the composite strata on the trough width coefficient(i).It is hypothesized that,in composite strata,the relationship between the trough width coefficient(i)and the stratum thickness(H)follows a piecewise linear trend.Specifically,within strata of identical elastic modulus(E),i exhibits a linear correlation with H,while variations in E affect the slope of this correlation.Building upon the non-iterative analytical method(NIAM)for evaluating tunnel excavation responses in composite strata,this study proposes two novel approaches:the crucial point method(CPM)and the standard curve method(SCM).These methods incorporate the elastic modulus into the estimation of i.The values of i obtained via NIAM and refined through CPM and SCM are validated against field data using the parameter K.The results are consistent with existing research findings,thereby confirming the reliability of the proposed methodology.Furthermore,the study investigates the relationship between tunnel depth(h0)and tunnel radius(R),and explores the interactions among the layer number of stratum(n),elastic modulus(E),and layer thickness(H).A reduction coefficient(η)is introduced to improve the model's accuracy.The proposed approach is applied to nine tunnel engineering cases,and comparisons with measured data demonstrate its accuracy and practical applicability.展开更多
摘要With the emergence of the concept of low-altitude economy and the continuous upgrading of avionics technology,cultivating aerospace professionals with single-chip microcomputer(SCM)knowledge and practical abilities has become an important reform direction for undergraduate education.From the perspective of course application,this paper explores the necessity of introducing SCM courses and reforming teaching methods for aerospace majors at the undergraduate level,and puts forward reform suggestions in teaching content,teaching methods,practical links,and evaluation systems.It aims to build a curriculum system that not only conforms to the characteristics of aerospace majors but also strengthens students’SCM engineering application literacy and cultivates applied compound talents for the aviation industry related to the low-altitude economy.
基金Software and System Engineering Research Center of Smart Car,Anhui Institute of Information Technology(Grant No.:23kjcxpt001)。
摘要With the gradual penetration of artificial intelligence technology into the field of education,to explore the application value of Generative Artificial Intelligence(AIGC)in traditional teaching,this paper sorts out the innovative application models of AIGC with the single-chip microcomputer course as the research object.By comparing and analyzing the teaching achievements of this course in the two academic years of 2024-2025,the effectiveness of AI empowerment in improving the teaching quality of single-chip microcomputers is verified.Meanwhile,based on the Back Propagation neural network algorithm,a prediction model for students’final exam scores is constructed by integrating multidimensional data such as students’classroom performance,experimental report scores,and phased test results.After training and verification,the prediction accuracy of the model on the test set reaches 76.9%.
摘要油田的水下控制模块液压系统长期处于高压、高温和腐蚀性环境下,面临着极高的故障风险。针对液压系统进行有效的故障诊断和预防性维护,研究将基于动态贝叶斯网络(Dynamic Bayesian Network,DBN)构建液压系统的故障诊断模型。实验结果表明,液压系统历史故障概率与实验预测的故障概率值均随时间的增加而增加。在T=0时,预测的液压系统故障概率值为0.106,与历史液压系统故障概率0.117非常接近;在T=20时,预测故障概率为0.194,历史故障概率为0.198,两者的诊断概率差值略有增加。此外,从T=0到T=20,模型故障诊断精确性均在85%以上,其中在T=0时的模型预测精确度最高为96.2%,T=20时,模型预测精确度最低为85.7%。研究表明,所提出的诊断模型在故障诊断时具有较好的精确性和稳定性,为油田水下控制模块(Subsea Control Module,SCM)液压系统的智能故障诊断提供一种新的解决方案。
基金Single-Chip Microcomputer and Interface Technology Project(Project No.:SYSJ2025032)。
摘要In recent years,research on industrial innovation and development has primarily focused on industrial automation and intelligent manufacturing.Within the field of integrating mechatronics and intelligent control,analyzing the efficient control of mechatronic systems enabled by generative AI for single-chip microcomputers can further highlight the value and significance of promoting AI technology applications.This paper examines the technical characteristics of generative AI in data generation,multimodal fusion,and dynamic adaptation,proposing lightweight model deployment strategies that compress large generative models to a range compatible with single-chip microcomputers,ensuring local real-time inference capabilities.It constructs an edge intelligent control architecture,enabling generative AI to directly participate in decision-making instruction generation,forming a new working system of perception,decision-making,and execution.Additionally,it designs a collaborative optimization training mechanism that leverages federated learning to overcome single-machine data limitations and enhance model generalization performance.At the application level,an intelligent fault prediction system is developed for early identification of equipment anomalies,an adaptive parameter optimization module is constructed for dynamically adjusting control strategies,and a multi-device collaborative scheduling engine is established to optimize production processes,providing technical support for embedded intelligent control in Industry 4.0 scenarios.
基金Single-Chip Microcomputer and Interface Technology Project(Project No.:SYSJ2025032)。
摘要In recent years,the application of various advanced technologies,such as digitization and informatization,has become the primary tool for innovation in education and teaching.For traditional single-chip microcomputer course teaching,it is necessary to emphasize the introduction and application of high-tech innovations in its path of innovative development.This course is a typical representative of multidisciplinary teaching,involving multiple disciplines such as electronic engineering,automation,and computer science.In response to issues faced in traditional teaching,such as rigid organization of teaching content that struggles to keep pace with technological advancements,resulting in a noticeable lag in knowledge transfer,and monotonous teaching methods that fail to precisely meet the diverse learning needs of students,analyzing the innovative applications of this course under the empowerment of AI technology holds significant practical relevance.In this regard,the study relies on AI technology empowerment to analyze the application paths for the deep integration of AI technology and single-chip microcomputer courses,constructing a new teaching model to provide references for enhancing teaching quality and stimulating students’innovative potential.
基金support from the National Natural Science Foundation of China(Grant No.52278387).
摘要This study investigates the influence of the elastic modulus(E)of the composite strata on the trough width coefficient(i).It is hypothesized that,in composite strata,the relationship between the trough width coefficient(i)and the stratum thickness(H)follows a piecewise linear trend.Specifically,within strata of identical elastic modulus(E),i exhibits a linear correlation with H,while variations in E affect the slope of this correlation.Building upon the non-iterative analytical method(NIAM)for evaluating tunnel excavation responses in composite strata,this study proposes two novel approaches:the crucial point method(CPM)and the standard curve method(SCM).These methods incorporate the elastic modulus into the estimation of i.The values of i obtained via NIAM and refined through CPM and SCM are validated against field data using the parameter K.The results are consistent with existing research findings,thereby confirming the reliability of the proposed methodology.Furthermore,the study investigates the relationship between tunnel depth(h0)and tunnel radius(R),and explores the interactions among the layer number of stratum(n),elastic modulus(E),and layer thickness(H).A reduction coefficient(η)is introduced to improve the model's accuracy.The proposed approach is applied to nine tunnel engineering cases,and comparisons with measured data demonstrate its accuracy and practical applicability.