Design and Development of Small Modular Courses for“Education-Training Integration”in Vocational Colleges:A Case Study

Vocational education plays a vital role in the development of skilled technical professionals and the advancement of the economy.However,the emphasis on campus education often neglects the importance of external training,hindering the overall development of vocational education.This study aims to address this issue by exploring the design and development of small modular courses that integrate training and education in vocational colleges,focusing on the mechanics course as a case study.The research methods employed in this study include an in-depth analysis of enterprise training needs,the development of digital teaching resources utilizing the finite element method(FEM),and the implementation of a small modular course integrating education and training.The data analysis reveals positive outcomes in terms of learners’comprehension and engagement with complex mechanics formulas through the use of stress nephograms and other digital resources.This research provides a new perspective on curriculum design and offers insights into the integration of training and education in vocational colleges.The findings underscore the significance of incorporating innovative teaching methodologies and digital resources in enhancing the quality and relevance of vocational education,ultimately contributing to the cultivation of skilled professionals and the growth of the vocational education sector.

Research on the Role of Guiding Students to Participate in Skills Competitions on the Development of Young Teachers in Vocational Colleges

This paper explores the role of guiding students to participate in skills competitions on the development of young teachers in vocational colleges.We investigate the impact of skills competitions on the consolidation of professional knowledge,development of innovation capabilities,improvement of hands-on abilities,and enhancement of communication skills with students.The results of this research demonstrate that skills competitions have a positive influence on the professional growth of young teachers.The consolidation of professional knowledge,development of innovation capabilities,improvement of hands-on abilities,and enhancement of communication skills collectively contribute to the effectiveness of young teachers in vocational colleges.It is recommended that vocational colleges prioritize and support the participation of young teachers in skills competitions to foster their professional development.

Improved Algorithm for Efficient Extraction of Relaxation Parameter Values from Wideband Permittivity of Baijiu

The complex permittivity of baijiu varies with frequency,and dielectric spectroscopy has been used to evaluate the quality.To simplify the analysis and reduce the number of the parameters,a dielectric relaxation model is often used to fit the permittivity data.However,existing fitting methods such as the least squares and particle swarm optimization methods are often computationally complex and require preset initial values.Therefore,a simpler calculation method of the relaxation parameters considering the geometric characteristics of the permittivity spectrum is proposed.It is based on the relationship between the Cole-Cole relaxation parameters and the Cole-Cole diagram,which is fitted by a geometric method.First,the concepts of the Cole-Cole parameters and the diagram are introduced,and then the process of obtaining the parameters from the complex permittivity measurement data is explained.Taking baijiu with 56%alcohol by volume(ABV)as an example,the fitting is better than the least squares method and similar to the particle swarm optimization.This method is then used for the parameter fitting of baijiu with ABV of 42-52%,and the average error is less than 1%,demonstrating its wider applicability.Finally,a prediction model is used for baijiu with 53%ABV,and the error is only 1.51%.Hence,the method can be applied to the measurement of ABV of baijiu.

Attention mechanism based multi-scale feature extraction of bearing fault diagnosis

Effective bearing fault diagnosis is vital for the safe and reliable operation of rotating machinery.In practical applications,bearings often work at various rotational speeds as well as load conditions.Yet,the bearing fault diagnosis under multiple conditions is a new subject,which needs to be further explored.Therefore,a multi-scale deep belief network(DBN)method integrated with attention mechanism is proposed for the purpose of extracting the multi-scale core features from vibration signals,containing four primary steps:preprocessing of multi-scale data,feature extraction,feature fusion,and fault classification.The key novelties include multi-scale feature extraction using multi-scale DBN algorithm,and feature fusion using attention mecha-nism.The benchmark dataset from University of Ottawa is applied to validate the effectiveness as well as advantages of this method.Furthermore,the aforementioned method is compared with four classical fault diagnosis methods reported in the literature,and the comparison results show that our pro-posed method has higher diagnostic accuracy and better robustness.

Passive Attack Detection for a Class of Stealthy Intermittent Integrity Attacks

This paper proposes a passive methodology for detecting a class of stealthy intermittent integrity attacks in cyberphysical systems subject to process disturbances and measurement noise.A stealthy intermittent integrity attack strategy is first proposed by modifying a zero-dynamics attack model.The stealthiness of the generated attacks is rigorously investigated under the condition that the adversary does not know precisely the system state values.In order to help detect such attacks,a backward-in-time detection residual is proposed based on an equivalent quantity of the system state change,due to the attack,at a time prior to the attack occurrence time.A key characteristic of this residual is that its magnitude increases every time a new attack occurs.To estimate this unknown residual,an optimal fixed-point smoother is proposed by minimizing a piece-wise linear quadratic cost function with a set of specifically designed weighting matrices.The smoother design guarantees robustness with respect to process disturbances and measurement noise,and is also able to maintain sensitivity as time progresses to intermittent integrity attack by resetting the covariance matrix based on the weighting matrices.The adaptive threshold is designed based on the estimated backward-in-time residual,and the attack detectability analysis is rigorously investigated to characterize quantitatively the class of attacks that can be detected by the proposed methodology.Finally,a simulation example is used to demonstrate the effectiveness of the developed methodology.

Improved lazy theta algorithm based on octree map for path planning of UAV

This paper investigates the path planning method of unmanned aerial vehicle(UAV)in threedimensional map.Firstly,in order to keep a safe distance between UAV and obstacles,the obstacle grid in the map is expanded.By using the data structure of octree,the octree map is constructed,and the search nodes is significantly reduced.Then,the lazy theta*algorithm,including neighbor node search,line-of-sight algorithm and heuristics weight adjustment is improved.In the process of node search,UAV constraint conditions are considered to ensure the planned path is actually flyable.The redundant nodes are reduced by the line-of-sight algorithm through judging whether visible between two nodes.Heuristic weight adjustment strategy is employed to control the precision and speed of search.Finally,the simulation results show that the improved lazy theta*algorithm is suitable for path planning of UAV in complex environment with multi-constraints.The effectiveness and flight ability of the algorithm are verified by comparing experiments and real flight.

Characteristics of the plasma sheath in helium discharge within dielectric tubes

To understand the characteristics of the plasma sheath within small tubes,a 2D numerical model of He discharge within dielectric tubes is developed.During plasma propagation for a tube diameter of 0.05 mm,the sheath thickness in the plasma head is almost equal to the tube radius.It decreases rapidly to several micrometers at an axial distance of 0.05 mm behind the plasma head,and then slightly increases and saturates at the axial position far behind the plasma head.A plasma-gas sheath surrounding the central plasma column is observed for a tube diameter equal to or greater than 0.8 mm.It is replaced by a plasma-wall sheath for smaller tubes.With the decrease in the tube diameter,the sheath thickness far behind the plasma head decreases while the ion flux increases significantly.However,when O_(2)gas with a proportion of 2%is added,both the sheath thickness and ion flux decrease.

Double-Layer-Optimizing Method of Hybrid Energy Storage Microgrid Based on Improved Grey Wolf Optimization

To reduce the comprehensive costs of the construction and operation of microgrids and to minimize the power fluctuations caused by randomness and intermittency in distributed generation,a double-layer optimizing configuration method of hybrid energy storage microgrid based on improved grey wolf optimization(IGWO)is proposed.Firstly,building a microgrid system containing a wind-solar power station and electric-hydrogen coupling hybrid energy storage system.Secondly,the minimum comprehensive cost of the construction and operation of the microgrid is taken as the outer objective function,and the minimum peak-to-valley of the microgrid’s daily output is taken as the inner objective function.By iterating through the outer and inner layers,the system improves operational stability while achieving economic configuration.Then,using the energy-self-smoothness of the microgrid as the evaluation index,a double-layer optimizing configuration method of the microgrid is constructed.Finally,to improve the disadvantages of grey wolf optimization(GWO),such as slow convergence in the later period and easy falling into local optima,by introducing the convergence factor nonlinear adjustment strategy and Cauchy mutation operator,an IGWO with excellent global performance is proposed.After testing with the typical test functions,the superiority of IGWO is verified.Next,using IGWO to solve the double-layer model.The case analysis shows that compared to GWO and particle swarm optimization(PSO),the IGWO reduced the comprehensive cost by 15.6%and 18.8%,respectively.Therefore,the proposed double-layer optimizationmethod of capacity configuration ofmicrogrid with wind-solar-hybrid energy storage based on IGWO could effectively improve the independence and stability of the microgrid and significantly reduce the comprehensive cost.

A Dual Source Power Based EV Wireless Charging System

Recently,there has been a huge increase in the usage of fuel resources for automobiles which is severely affecting the climate and causing global warming.The use of electric vehicle(EV)is an effective way to protect the environment and reduce travel costs.However,the EV charging system has a single charging source,and the charging rate is limited.In this paper,an EV wireless charging system based on dual source power supply has been developed.It realizes intelligent switching between 12 V photovoltaic output and 220 V AC dual source power,and has wireless transmission function.Based on the proposed power supply architecture,the micro wireless charging model is built,which enables the EV model to store power and realize static and mobile control through the wireless induction charging system.

State Estimation Method for GNSS/INS/Visual Multi-sensor Fusion Based on Factor Graph Optimization for Unmanned System

With the development of unmanned driving technology,intelligent robots and drones,high-precision localization,navigation and state estimation technologies have also made great progress.Traditional global navigation satellite system/inertial navigation system(GNSS/INS)integrated navigation systems can provide high-precision navigation information continuously.However,when this system is applied to indoor or GNSS-denied environments,such as outdoor substations with strong electromagnetic interference and complex dense spaces,it is often unable to obtain high-precision GNSS positioning data.The positioning and orientation errors will diverge and accumulate rapidly,which cannot meet the high-precision localization requirements in large-scale and long-distance navigation scenarios.This paper proposes a method of high-precision state estimation with fusion of GNSS/INS/Vision using a nonlinear optimizer factor graph optimization as the basis for multi-source optimization.Through the collected experimental data and simulation results,this system shows good performance in the indoor environment and the environment with partial GNSS signal loss.

Research on Condenser Deterioration Evolution Trend Based on ANP-EWM Fusion Health Degree

This study presents a proposed method for assessing the condition and predicting the future status of condensers operating in seawater over an extended period.The aim is to address the problems of scaling and corrosion,which lead to increased loss of cold resources.The method involves utilising a set of multivariate feature parameters associated with the condenser as input for evaluation and trend prediction.This methodology offers a precise means of determining the optimal timing for condenser cleaning,with the ultimate goal of improving its overall performance.The proposed approach involves the integration of the analytic network process with subjective expert experience and the entropy weightmethod with objective big data analysis to develop a fusion health degreemodel.The mathematical model is constructed quantitatively using the improved Mahalanobis distance.Furthermore,a comprehensive prediction model is developed by integrating the improved Informer model and Markov error correction.This model takes into account the health status of the equipment and several influencing factors,includingmultivariate feature characteristics.This model facilitates the objective examination and prediction of the progression of equipment deterioration trends.The present study involves the computation and verification of the field time series data,which serves to demonstrate the accuracy of the condenser health-related models proposed in this research.These models effectively depict the real condition and temporal variations of the equipment,thus offering a valuable method for determining the precise cleaning time required for the condenser.

Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power Systems

This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.

Practical prescribed-time fuzzy tracking control for uncertain nonlinear systems with time-varying actuators faults

The paper investigates the practical prescribed-time fuzzy tracking control problem for a category of nonlinear system subject to time-varying actuator faults.The presence of unknown nonlinear dynamics and actuator faults makes achieving tracking control within a prescribed-time challenging.To tackle this issue,we propose a novel practical prescribed-time fuzzy tracking control strategy,which is independent of the initial state of the system and does not rely on precise modeling of the system and actuators.We apply the approximation capabilities of fuzzy logic systems to handle the unknown nonlinear functions and unidentified actuator faults in the system.The piecewise controller and adaptive law constructed based on piecewise prescribed time-varying function and backstepping technique method establish the theoretical framework of practical prescribed-time tracking control,and extend the range of prescribed-time tracking control to infinity.Regardless of the initial conditions,the proposed control strategy can guarantee that all signals remain uniformly bounded within the practical prescribed time in the presence of unknown nonlinear item and time-varying actuator faults.Simulation example is presented to demonstrate the effectiveness of the proposed control strategy.

Modeling and Backstepping-based Nonlinear Control Strategy for a 6 DOF Quadrotor Helicopter

In this article, a nonlinear model of an underactuated six degrees of freedom （6 DOF） quadrotor helicopter is derived on the basis of the Newton-Euler formalism. The derivation comprises determining equations of the motion of the quadrotor in three dimensions and approximating the actuation forces through the modeling of aerodynamic coefficients and electric motor dynamics. The derived model composed of translational and rotational subsystems is dynamically unstable, so a sequential nonlinear control strategy is used. The control strategy includes feedback linearization coupled with a PD controller for the translational subsystem and a backstepping-based PID nonlinear controller for the rotational subsystem of the quadrotor. The performances of the nonlinear control method are evaluated by nonlinear simulation and the results demonstrate the effectiveness of the proposed control strategy for the quadrotor helicopter in quasi-stationary flights.

Air combat decision-making of multiple UCAVs based on constraint strategy games

Game theory can be applied to the air combat decision-making problem of multiple unmanned combat air vehicles(UCAVs).However,it is difficult to have satisfactory decision-making results completely relying on air combat situation information,because there is a lot of time-sensitive information in a complex air combat environment.In this paper,a constraint strategy game approach is developed to generate intelligent decision-making for multiple UCAVs in complex air combat environment with air combat situation information and time-sensitive information.Initially,a constraint strategy game is employed to model attack-defense decision-making problem in complex air combat environment.Then,an algorithm is proposed for solving the constraint strategy game based on linear programming and linear inequality(CSG-LL).Finally,an example is given to illustrate the effectiveness of the proposed approach.

Effect of diode-laser parameters on shear force of micro-joints soldered with Sn-Ag-Cu lead-free solder on Au/Ni/Cu pad

Soldering experiments with Sn-3.5Ag-0.5Cu lead-free solder on Au/Ni/Cu pad were carried out by means of diode-laser and IR reflow soldering methods respectively.The influence of different heating methods as well as output power of diode-laser on shear force of micro-joints was studied and the relationship between the shear force and microstructures of micro-joints was analyzed.The results indicate that the formation of intermetallic compound Ag3Sn is the key factor to affect the shear force and the fine eutectic network structures of micro-joints as well as the dispersion morphology of fine compound Ag3Sn,in which eutectic network band is responsible for the improvement of the shear force of micro-joints soldered with Sn-Ag-Cu lead-free solder.With the increases of output power of diode-laser,the shear force and the microstructures change obviously.The eutectic network structures of micro-joints soldered with diode-laser soldering method are more homogeneous and the grains of Ag3Sn compounds are finer in the range of near optimal output power than those soldered with IR reflow soldering method,so the shear force is also higher than that using IR reflow soldering method.When the output power value of diode-laser is about 41.0 W,the shear force exhibits the highest value that is 70% higher than that using IR reflow soldering method.

A New Criterion of Fault Estimation for Neutral Delay Systems Using Adaptive Observer

这份报纸用适应观察员学习中立延期系统的差错评价的问题。一个新奇快适应差错评价(FAFE ) 算法首先基于适应观察员被建议包括快和精确性提高差错评价的表演。同时，一个延期依赖者标准被建立特别为小延期系统减少设计过程的保守主义。然后，全面分析被介绍用线性矩阵不平等(LMI ) 讨论精明的步技术。最后，模拟结果被介绍说明建议算法的效率。

Adaptively Robust Phase Lock Loop for Low C/N Carrier Tracking in a GPS Software Receiver

在 GPS 应用程序的一个重要问题是怎么追踪 GPS (全球放系统) 在低 carrier-to-noise 比率(C/N ) 下面精确并且连续地发信号。在这份报纸，一个适应地柔韧的过滤器基于低 C/N 搬运人阶段锁循环(PLL ) 在一个 GPS 软件接收装置平台下面被开发。就传统的追踪循环上的低 C/N 搬运人信号的效果而言，追踪循环的平行关联被建立。一个线性最佳的评估者被设计在 kinematics 模型和大小处理依赖噪音。而且，一个适应地柔韧的过滤器基于三片断功能被设计调整因素。当收到的信号在有利条件下面时，新过滤器的表演很类似于一个标准 Kalman 过滤器。为追踪的一个实际弱搬运人，这新提高的 PLL 聪明地根据全部的阶段神经质分析调节循环参数。它成功地由适应地平衡更新的动态模型状态和大小的影响抵抗孤立点和动态模型错误。新过滤器的坚韧性和效率被测试实验的一些真实数据表明。结果证实有追踪循环的这个适应地柔韧的阶段的阶段错误的标准差能在 24 dB-Hz 附近与卫星 C/N 比率到达 0.01 个周期，它显著地改进表演。

PID-type fault-tolerant prescribed performance control of fixed-wing UAV

This paper introduces a fault-tolerant control(FTC)design for a faulty fixed-wing unmanned aerial vehicle(UAV).To constrain tracking errors against actuator faults,error constraint inequalities are first transformed to a new set of variables based on prescribed performance functions.Then,the commonly used and powerful proportional-integral-derivative(PID)control concept is employed to filter the transformed error variables.To handle the fault-induced nonlinear terms,a composite learning algorithm consisting of neural network and disturbance observer is incorporated for increasing flight safety.It is shown by Lyapunov stability analysis that the tracking errors are strictly constrained within the specified error bounds.Experimental results are presented to verify the feasibility of the developed FTC scheme.

Tradeoff Analysis of Factors Affecting Longitudinal Carrier Landing Performance for Small UAV Based on Backstepping Controller

Tradeoff analysis of the factors,including external environment and unmanned aerial vehicle(UAV)aerodynamic attributes,which affect longitudinal carrier landing performance,is important for small UAV.First,small UAV longitudinal carrier landing system is established,as well as the nonlinear dynamics and kinematics model,and then the longitudinal flight control system using backstepping technology with minimum information about the aerodynamic is designed.To assess the landing performance,a variety of influencing factors are considered,resulting in the constraints of aerodynamic attributes of carrier UAV.The simulation results show that the severe sea condition has the greatest influence on landing dispersion,while air wake is the primary factor on impact velocity.Among the longitudinal aerodynamic parameters,the lift curve slope is the most important factor affecting the landing performance,and increasing lift curve slope can improve the landing performance significantly.A better system performance will be achieved when the lift curve slope is larger than 2per radian.