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Study on failure of single-bolt double-lap composite joints based on test and numerical emulation 基于试验与数值模拟的单螺栓双搭接复合节点破坏研究
Q3 Engineering Pub Date : 2023-06-01 DOI: 10.1051/jnwpu/20234130471
Yan Huang, Feixiang Ren, Puhui Chen
In order to study the mechanical properties of ZT7G/LT-03A carbon fiber reinforced composite bolted joints, the single-bolt double-lap joints tests were carried out with 3 kinds of ply and 3 kinds of width, and the effects of the different ply ratios, width to diameter ratios on the failure load and failure mode were analyzed. Then, the failure process of the specimens was simulated by using the progressive damage and failure analysis method. The failure mode and failure load of the model are consistent with that of the specimen, which verified the accuracy of the model. On this basis, the stress and damage status of each ply during initial load shedding were studied, and the influence of the ply ratios and width to diameter ratios on the performance of laminates was further studied. The results show that when the width to diameter ratio of laminates increases, the failure mode changes from tensile failure to bearing failure, and to change the ply ratios does not affect the failure mode in a certain range.
为了研究ZT7G/LT-03A碳纤维增强复合材料螺栓连接的力学性能,进行了3种厚度和3种宽度的单螺栓双搭接连接试验,分析了不同厚度比、宽径比对破坏载荷和破坏模式的影响。然后,采用渐进式损伤和破坏分析方法对试件的破坏过程进行了模拟。模型的破坏模式和破坏载荷与试件的破坏模式和破坏载荷一致,验证了模型的准确性。在此基础上,研究了层合板在初始减载过程中各层的应力和损伤状态,并进一步研究了层合板的层合比和宽径比对层合板性能的影响。结果表明:当层合板的宽径比增大时,层合板的破坏模式由拉伸破坏转变为承载破坏,在一定范围内改变层合板的厚度比不影响层合板的破坏模式;
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引用次数: 0
Optimal design of SMA linear actuation unlocking mechanism for CubeSat 立方体卫星SMA线性驱动解锁机构的优化设计
Q3 Engineering Pub Date : 2023-06-01 DOI: 10.1051/jnwpu/20234130510
Peng Li, Juanni Yin, Jiaolong Zhang, Z. Gao, Heng Huang
In order to realize the reliable unlocking of solar arrays of a CubeSat under the strict constraints of space and power dissipation, a shape memory alloy(SMA) wire linear actuation unlocking mechanism is developed. Through using a spring-SMA structure, relying on the spring force locking, heating the SMA wire and producing a recovery stress drive pin movement, the solar arrays are unlocked. The mathematical model of the unlocking mechanism is established, and the relationship among stroke, unlocking time, power, alloy wire diameter and working voltage of the SMA unlocking mechanism is obtained through simulation. In order to optimize its overall unlocking time and power, the particle swarm optimization algorithm is used to optimize the diameter and working voltage of the alloy wire. The simulation results show that the SMA unlocking mechanism with the wire whose diameter is 0.5 mm has the best working performance when the driving voltage is 1.2 V. Finally, the experimental study of the design results shows that the unlocking time of the actuation unlocking mechanism is 3.2 s, its power is 3.55 W and that its pin-pulling stroke is 1.8 mm, being consistent with the simulation results. The unlocking mechanism has a high reliability, consistent working performance and good adaptability, therefore having passed various environmental tests and being successfully applied to a CubeSat in orbit.
为了在空间和功耗的严格约束下实现立方体卫星太阳能电池阵列的可靠解锁,开发了一种形状记忆合金(SMA)线线性驱动解锁机构。通过使用弹簧SMA结构,依靠弹簧力锁定,加热SMA线并产生恢复应力驱动销运动,解锁太阳能电池阵列。建立了SMA解锁机构的数学模型,通过仿真得到了SMA解锁装置的行程、解锁时间、功率、合金线直径和工作电压之间的关系。为了优化其整体解锁时间和功率,采用粒子群优化算法对合金丝的直径和工作电压进行了优化。仿真结果表明,当驱动电压为1.2V时,直径为0.5mm的SMA解锁机构具有最佳的工作性能。最后,对设计结果的实验研究表明,驱动解锁机构的解锁时间为3.2s,功率为3.55W,拔销行程为1.8mm,与仿真结果一致。该解锁机构可靠性高,工作性能稳定,适应性强,通过了各种环境测试,并成功应用于在轨立方体卫星。
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引用次数: 0
Research on a class-incremental learning method based on sonar images 基于声纳图像的类增量学习方法研究
Q3 Engineering Pub Date : 2023-04-01 DOI: 10.1051/jnwpu/20234120303
Xinzhe Chen, Hong Liang, Weiyu Xu
Due to the low resolution and the small number of samples of sonar images, the existing class incremental learning networks have a serious problem of catastrophic forgetting of historical task targets, resulting in a low average recognition rate of all task targets. Based on the framework model of generated replay, an improved class incremental learning network is proposed in this paper, and a new deep convolution generative adversarial network is designed and built to replace the variational autoencoder as the reconstruction model of generated replay incremental network to improve the effect of image reconstruction; a new convolution neural network is constructed to replace the multi-layer perception as the recognition network of generated replay incremental network to improve the performance of image classification and recognition. The results show that the improved generated replay incremental network alleviates the problem of catastrophic forgetting of historical task targets, and the average recognition rate for all task targets is significantly improved.
由于声纳图像的分辨率低、样本数量少,现有的类增量学习网络存在严重的历史任务目标灾难性遗忘问题,导致所有任务目标的平均识别率较低。基于生成回放的框架模型,本文提出了一种改进的类增量学习网络,并设计和构建了一种新的深度卷积生成对抗性网络,以取代变分自动编码器作为生成回放增量网络的重建模型,提高图像重建效果;构造了一种新的卷积神经网络来代替多层感知作为生成的重放增量网络的识别网络,以提高图像分类和识别的性能。结果表明,改进的生成重放增量网络缓解了历史任务目标的灾难性遗忘问题,所有任务目标的平均识别率都显著提高。
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引用次数: 0
Landing gear condition monitoring based on back propagation neural network-based on multi-strategy cooperative optimization 基于反向传播神经网络的多策略协同优化起落架状态监测
Q3 Engineering Pub Date : 2023-04-01 DOI: 10.1051/jnwpu/20234120264
Yunwen Feng, Rui Wang, Tao Lu, Jun-Yu Chen, Cheng Lu
To effectively monitor the operation state of landing gear, a back propagation neural network-based on multi-strategy cooperative optimization(MSCO-BPNN) is proposed. The multi-strategy optimization algorithm is composed of chaotic mapping strategy, adaptive spiral capture strategy, crossover mutation strategy and whale optimization algorithm(WOA). WOA is applied to find the optimal hyperparameters of back propagation neural network(BPNN). The search efficiency, multi-local search ability and global search performance of model can be improved by using chaotic mapping strategy, adaptive spiral capture strategy and crossover mutation strategy. The BPNN with optimal hyperparameters is introduced to establish the implicit model of input parameters and output responses. Based on quick access recorder(QAR) data, landing gear left side brake temperature is act as the monitoring objective of this paper. The validity and applicability of MSCO-BPNN are verified by compared with WOA-BPNN, particle swarm optimization BPNN and traditional BPNN. The results show that MSCO-BPNN can monitor the operation status of landing gear with high efficiency and accuracy. The efforts of this paper provide a promising insight for the precise condition monitoring of complex structures.
为了有效监测起落架的运行状态,提出了一种基于多策略协同优化的反向传播神经网络(msc - bpnn)。多策略优化算法由混沌映射策略、自适应螺旋捕获策略、交叉突变策略和鲸鱼优化算法(WOA)组成。将WOA用于寻找反向传播神经网络(BPNN)的最优超参数。采用混沌映射策略、自适应螺旋捕获策略和交叉突变策略可以提高模型的搜索效率、多局部搜索能力和全局搜索性能。引入带最优超参数的bp神经网络,建立了输入参数和输出响应的隐式模型。本文以快速存取记录仪(QAR)数据为基础,以起落架左侧制动温度为监测目标。通过与WOA-BPNN、粒子群优化BPNN和传统BPNN的比较,验证了MSCO-BPNN的有效性和适用性。结果表明,该方法能够高效、准确地监测起落架的运行状态。本文的工作为复杂结构的精确状态监测提供了有希望的见解。
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引用次数: 0
A combined aerodynamic parameter identification method for missing test data 试验数据缺失的气动参数组合识别方法
Q3 Engineering Pub Date : 2023-04-01 DOI: 10.1051/jnwpu/20234120282
Yang Liu, Chunna Li, Yuan Fang, Chun-lin Gong
In order to solve the problem that some test data cannot be measured or the measurement is difficult, a combined aerodynamic parameters identification method for missing test data is proposed. In this method, the aerodynamic parameter identification problem is modified into an optimization problem. The initial value of the flight state and the aerodynamic parameter interpolation table are used as design variables, and the motion equation of the aircraft including all aerodynamic parameters is used as a model to construct an objective function containing multiple pieces of test data information. In the optimization, the aerodynamic parameter database and the identification results of the existing methods are used as the prior knowledge. The initial value of the unmeasured data is fitted as the reference value. Then, the feasible sample selection method is designed. Finally, the differential evolution algorithm is used to solve the problem. The proposed method is used to process 264 pieces of test data, and the results show that compared with the existing aerodynamic parameter identification methods, the proposed identification method can obtain all aerodynamic parameters with higher accuracy and can inversely calculate and obtain unmeasured flight test data practical engineering significance.
为解决部分试验数据无法测量或测量困难的问题,提出了一种缺失试验数据气动参数联合识别方法。该方法将气动参数辨识问题转化为优化问题。以飞行状态初值和气动参数插值表为设计变量,以包含所有气动参数的飞机运动方程为模型,构建包含多段试验数据信息的目标函数。在优化过程中,使用气动参数数据库和现有方法的辨识结果作为先验知识。拟合未测数据的初值作为参考值。然后,设计了可行的样本选择方法。最后,采用差分进化算法对该问题进行求解。对264条试验数据进行了处理,结果表明,与现有的气动参数识别方法相比,所提出的识别方法能以更高的精度获得所有气动参数,并能反算获得未测飞行试验数据,具有实际工程意义。
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引用次数: 0
Path tracking control of solar-powered UAV based on energy management strategy 基于能量管理策略的太阳能无人机路径跟踪控制
Q3 Engineering Pub Date : 2023-04-01 DOI: 10.1051/jnwpu/20234120409
Lin Guo, Fei Liu, Jiayu Li, Pei He, Qingdong Li, Jiwei Wang, Yangming Guo
To coordinate the conflict between the high-altitude task and long-term energy efficiency of high-altitude long endurance solar UAV, it is one of the core issues of UAV control. A strategy combining the energy management with the route tracking is presented. Firstly, based on the three-dimensional particle motion model, energy storage battery model and solar energy acquisition model for the solar UAV, according to the aerodynamic parameters of the solar UAV and the typical horizontal flight, climb, descent and other motion processes of the solar UAV, the energy management strategy of the solar UAV is designed, and the allocation mechanism and optimal flight parameters of the energy acquisition, storage and consumption of the solar UAV in different flight stages are determined. The surplus solar energy is stored by using the gravitational potential energy, and then the energy management based on height adjustment is carried out to realize the longitudinal tracking control of the solar UAV under different lighting and energy conditions. Then based on the task requirements of the lateral movement of the solar UAV, a track tracking control method based on the feedback linearization method is established by decoupling the particle dynamics equation of the solar UAV, and the track tracking control of the solar UAV in the lateral direction is realized. Finally, a simulation throughout 24 hours is implemented and illustrated the effectiveness of the energy management strategy and route tracking control law.
协调高空长航时太阳能无人机的高空任务与长期能效之间的冲突,是无人机控制的核心问题之一。提出了一种将能量管理与路径跟踪相结合的策略。首先,基于太阳能无人机的三维粒子运动模型、储能电池模型和太阳能获取模型,根据太阳能无人机空气动力学参数和太阳能无人机典型的水平飞行、爬升、下降等运动过程,设计了太阳能无人机能量管理策略,确定了太阳能无人机在不同飞行阶段的能量获取、储存和消耗的分配机制和最佳飞行参数。利用重力势能储存剩余的太阳能,然后进行基于高度调节的能量管理,实现太阳能无人机在不同照明和能量条件下的纵向跟踪控制。然后,根据太阳能无人机横向运动的任务要求,通过解耦太阳能无人机的粒子动力学方程,建立了基于反馈线性化方法的轨迹跟踪控制方法,实现了太阳能无人机在横向方向上的轨迹跟踪控制。最后,通过24小时的仿真验证了能量管理策略和路径跟踪控制律的有效性。
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引用次数: 0
Study on learning algorithm of transfer reinforcement for multi-agent formation control 多智能体群体控制传递强化学习算法研究
Q3 Engineering Pub Date : 2023-04-01 DOI: 10.1051/jnwpu/20234120389
Penglin Hu, Q. Pan, Yaning Guo, Chunhui Zhao
Considering the obstacle avoidance and collision avoidance for multi-agent cooperative formation in multi-obstacle environment, a formation control algorithm based on transfer learning and reinforcement learning is proposed. Firstly, in the source task learning stage, the large storage space required by Q-table solution is avoided by using the value function approximation method, which effectively reduces the storage space requirement and improves the solving speed of the algorithm. Secondly, in the learning phase of the target task, Gaussian clustering algorithm was used to classify the source tasks. According to the distance between the clustering center and the target task, the optimal source task class was selected for target task learning, which effectively avoided the negative transfer phenomenon, and improved the generalization ability and convergence speed of reinforcement learning algorithm. Finally, the simulation results show that this method can effectively form and maintain formation configuration of multi-agent system in complex environment with obstacles, and realize obstacle avoidance and collision avoidance at the same time.
考虑到多障碍环境下多智能体协同编队的避障和防撞问题,提出了一种基于迁移学习和强化学习的编队控制算法。首先,在源任务学习阶段,使用值函数近似方法避免了Q表求解所需的大存储空间,有效地降低了存储空间需求,提高了算法的求解速度。其次,在目标任务的学习阶段,采用高斯聚类算法对源任务进行分类。根据聚类中心与目标任务的距离,选择最优的源任务类进行目标任务学习,有效避免了负迁移现象,提高了强化学习算法的泛化能力和收敛速度。最后,仿真结果表明,该方法能够在有障碍物的复杂环境中有效地形成和保持多智能体系统的编队配置,同时实现避障和防撞。
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引用次数: 0
A novel bearing fault diagnosis method based on multi-scale transfer symbolic dynamic entropy and support vector machine 基于多尺度传递符号动态熵和支持向量机的轴承故障诊断方法
Q3 Engineering Pub Date : 2023-04-01 DOI: 10.1051/jnwpu/20234120344
Guangwei YU, Li YAN
In view of the problem that the generalization ability of traditional data-driven fault diagnosis model declines or even fails in mechanical system diagnosis, a fault diagnosis method based on multi-scale transfer symbolic dynamic entropy and support vector machine is proposed based on the idea of transfer learning. Firstly, multi-scale symbolic dynamic entropy is used to extract fault features from measured vibration signals. And then a feature projection technique based on transfer learning is proposed, which reduces the data distribution difference. Secondly, the parameters of the multi-scale transfer symbol dynamic entropy method are optimized to improve the final fault identification rate. Then, the support vector machine can implement the fault identification. Finally, through the test of bearing fault experimental signals, the rolling bearing diagnosis method based on multi-scale transfer symbol dynamic entropy can effectively improve the generalization ability of data-driven model and realize accurate identification of different fault types of rolling bearing under a small number of samples.
首先,利用多尺度符号动态熵从实测振动信号中提取故障特征;然后提出了一种基于迁移学习的特征投影技术,减小了数据分布差异。其次,对多尺度传递符号动态熵法的参数进行优化,提高最终故障识别率;然后,利用支持向量机实现故障识别。最后,通过对轴承故障实验信号的测试,基于多尺度传递符号动态熵的滚动轴承诊断方法能够有效提高数据驱动模型的泛化能力,实现在少量样本下对滚动轴承不同故障类型的准确识别。
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引用次数: 0
Characteristic analysis and filtering algorithm design for UNGM model UNGM模型的特征分析与滤波算法设计
Q3 Engineering Pub Date : 2023-04-01 DOI: 10.1051/jnwpu/20234120293
Shan Lu, Shiyuan Zhang
The univariate non-stationary growth model (UNGM) is widely used in the verification of nonlinear filters, and the unscented Kalman filter (UKF) is often used as the reference filter for comparative analysis when using this model to evaluate the filter performance. However, due to the strong nonlinearity of UNGM and the change of model properties with different parameter settings, the estimation misalignment problem due to different reasons will occur when UKF is used for filtering. To solve these problems, this paper analyzes the complex characteristics of UNGM in filtering process, and proposes an UKF with sliding sampling module(SSUKF). The algorithm is optimized on the basis of UKF, and can effectively deal with the complex characteristics of UNGM by sampling and analyzing the filtering information in the filtering process and correcting the distribution of Sigma points in real time. SSUKF is applied to UNGM under different parameters and compared with UKF and bootstrap particle filter(BPF). The simulation results show that SSUKF can effectively solve the misalignment problem when UKF is applied to UNGM, and the calculation speed is better than BPF. Compared with UKF, SSUKF is suitable as a benchmark filter for evaluating the performance of nonlinear filters using UNGM.
单变量非平稳增长模型(UNGM)被广泛应用于非线性滤波器的验证中,而unscented卡尔曼滤波器(UKF)在使用该模型评价滤波器性能时常被用作参考滤波器进行对比分析。然而,由于UNGM的强非线性和模型属性随参数设置的不同而变化,在使用UKF进行滤波时会出现由于不同原因导致的估计失调问题。针对这些问题,分析了UNGM在滤波过程中的复杂特性,提出了一种带滑动采样模块的UKF (SSUKF)。该算法在UKF的基础上进行了优化,通过对滤波过程中的滤波信息进行采样和分析,实时校正Sigma点的分布,可以有效地处理UNGM的复杂特性。将SSUKF应用于不同参数下的UNGM,并与UKF和bootstrap particle filter(BPF)进行了比较。仿真结果表明,当UKF应用于UNGM时,SSUKF可以有效地解决不对准问题,且计算速度优于BPF。与UKF相比,SSUKF适合作为评价UNGM非线性滤波器性能的基准滤波器。
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引用次数: 0
Research on configuration and performance of water ramjet pressurized water intake system 水冲压发动机增压进水系统结构与性能研究
Q3 Engineering Pub Date : 2023-04-01 DOI: 10.1051/jnwpu/20234120310
Haojie Yang, Kai Luo, Chuang Huang, Zhao Liu, Xu He, Qian Wang
Water ramjet is the most ideal power propulsion device for high-speed underwater weapons. However, failure to start it at low-speed makes it hard for the engine to be widely used. In order to solve the problem of starting water ramjet at low-speed, a configuration scheme of water ramjet pressurized water intake system of the micro-turbine driving micro-mixed-flow pump is proposed. The design method of micro-turbine and micro-mixed-flow pump is perfected. And the simulation model of turbine and mixed-flow pump is established. The rationality of the design results was verified by numerical simulation. The matching design of the turbine and the mixed-flow pump is completed. And the working performance of the pressurized water inlet system is analyzed. The results show that the maximum relative deviation between the design results of the turbine and the pump and the target value is less than 3.2%, and the booster system can increase the fluid pressure by 2.0 MPa, reducing the starting speed of the ramjet from 90 to 63 m/s. The research results of this paper have reference value for the engineering application of water ramjet technology.
水冲压发动机是高速水下武器最理想的动力推进装置。然而,由于低速启动失败,使得该发动机难以广泛使用。为解决水冲压发动机低速起动问题,提出了一种微涡轮驱动微混流泵水冲压发动机增压进水系统的配置方案。完善了微型涡轮和微型混流泵的设计方法。建立了汽轮机和混流泵的仿真模型。通过数值模拟验证了设计结果的合理性。完成了水轮机与混流泵的匹配设计。分析了增压进水系统的工作性能。结果表明,涡轮和泵的设计结果与目标值的最大相对偏差小于3.2%,增压系统可将流体压力提高2.0 MPa,将冲压发动机的启动速度从90 m/s降低到63 m/s。本文的研究成果对水冲压发动机技术的工程应用具有参考价值。
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引用次数: 0
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西北工业大学学报
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