The ammunition loading system manipulator is susceptible to gear failure due to high-frequency,heavyload reciprocating motions and the absence of protective gear components.After a fault occurs,the distribution of fau...The ammunition loading system manipulator is susceptible to gear failure due to high-frequency,heavyload reciprocating motions and the absence of protective gear components.After a fault occurs,the distribution of fault characteristics under different loads is markedly inconsistent,and data is hard to label,which makes it difficult for the traditional diagnosis method based on single-condition training to generalize to different conditions.To address these issues,the paper proposes a novel transfer discriminant neural network(TDNN)for gear fault diagnosis.Specifically,an optimized joint distribution adaptive mechanism(OJDA)is designed to solve the distribution alignment problem between two domains.To improve the classification effect within the domain and the feature recognition capability for a few labeled data,metric learning is introduced to distinguish features from different fault categories.In addition,TDNN adopts a new pseudo-label training strategy to achieve label replacement by comparing the maximum probability of the pseudo-label with the test result.The proposed TDNN is verified in the experimental data set of the artillery manipulator device,and the diagnosis can achieve 99.5%,significantly outperforming other traditional adaptation methods.展开更多
针对可重复使用飞行器热防护结构在复杂多场耦合环境下易产生层间脱粘损伤的关键问题,提出基于超声导波与域自适应迁移学习的无损检测方法。通过设计4类典型粘接缺陷的隔热瓦试件,结合双向正交扫描策略与超声激励–接收机制,实现粘接区...针对可重复使用飞行器热防护结构在复杂多场耦合环境下易产生层间脱粘损伤的关键问题,提出基于超声导波与域自适应迁移学习的无损检测方法。通过设计4类典型粘接缺陷的隔热瓦试件,结合双向正交扫描策略与超声激励–接收机制,实现粘接区域的高效覆盖检测。针对试件个体差异引起的信号漂移问题,采用基于峰值比例阈值的相位对齐方法,通过优化窗口长度同步保留损伤敏感特征并抑制噪声干扰。进一步构建域自适应迁移学习网络(Domain-adaptive transfer learning,DATL),实现跨试件损伤特征的分布对齐。试验表明,在跨试件测试场景下,DATL模型准确率仅下降3.9%,域间分布差异指数从0.31降至0.10;在目标域数据量不足40%时,其准确率仍达85%,较卷积神经网络(Convolutional neural network,CNN)提升19.4%。该方法缓解了对损伤类型和试件一致性的依赖,可降低在役热防护结构脱粘检测的误报率与漏检率,为可重复使用飞行器的快速无损检测与健康评估提供了一种可行的解决参考方案。展开更多
针对单相矩阵式无线电能传输MC-WPT(matrix converter based wireless power transfer)系统网侧电流谐波含量大的问题,提出1种谐波抑制调制策略,可有效降低网侧电流低次谐波含量及总谐波失真度THD(total harmonic distortion)。分析谐...针对单相矩阵式无线电能传输MC-WPT(matrix converter based wireless power transfer)系统网侧电流谐波含量大的问题,提出1种谐波抑制调制策略,可有效降低网侧电流低次谐波含量及总谐波失真度THD(total harmonic distortion)。分析谐振槽电压电流特性,基于参数归一化方法得到2个基波分量的等效电路,进而推导出MC-WPT的数学模型。在此基础上,以消除低次谐波含量为目标,应用计算法得到接收侧H桥的优化调制波,使网侧电流低频成分仅有工频分量,从而降低网侧电流THD。最后搭建实验平台,验证所提谐波抑制调制策略的可行性与有效性。展开更多
文中以非隔离型柔性互联配电网为研究对象,针对交流系统发生单相接地故障时,因零序分量传递特性导致的典型接地故障检测方法适应性问题开展研究。首先,建立非隔离型智能软开关(soft open point, SOP)的零序等值拓扑网络,提出零序分量的...文中以非隔离型柔性互联配电网为研究对象,针对交流系统发生单相接地故障时,因零序分量传递特性导致的典型接地故障检测方法适应性问题开展研究。首先,建立非隔离型智能软开关(soft open point, SOP)的零序等值拓扑网络,提出零序分量的传递方程并定量分析零序分量传递至非故障侧的大小,分析不同场景下零序分量抑制效果;然后,分别对小电流互联系统、小电阻互联系统、小电流和小电阻互联系统的典型保护进行适应性分析,结果表明,在非隔离型柔性互联系统中,零序分量传递至系统健全侧后保护可能发生误动或误告警;最后,基于PSCAD建立典型非隔离型柔性互联配电网模型,对不同互联系统的保护适应性分析进行验证。文中研究结论可为非隔离型柔性互联配电网的保护配置提供理论支撑。展开更多
文摘The ammunition loading system manipulator is susceptible to gear failure due to high-frequency,heavyload reciprocating motions and the absence of protective gear components.After a fault occurs,the distribution of fault characteristics under different loads is markedly inconsistent,and data is hard to label,which makes it difficult for the traditional diagnosis method based on single-condition training to generalize to different conditions.To address these issues,the paper proposes a novel transfer discriminant neural network(TDNN)for gear fault diagnosis.Specifically,an optimized joint distribution adaptive mechanism(OJDA)is designed to solve the distribution alignment problem between two domains.To improve the classification effect within the domain and the feature recognition capability for a few labeled data,metric learning is introduced to distinguish features from different fault categories.In addition,TDNN adopts a new pseudo-label training strategy to achieve label replacement by comparing the maximum probability of the pseudo-label with the test result.The proposed TDNN is verified in the experimental data set of the artillery manipulator device,and the diagnosis can achieve 99.5%,significantly outperforming other traditional adaptation methods.
文摘针对可重复使用飞行器热防护结构在复杂多场耦合环境下易产生层间脱粘损伤的关键问题,提出基于超声导波与域自适应迁移学习的无损检测方法。通过设计4类典型粘接缺陷的隔热瓦试件,结合双向正交扫描策略与超声激励–接收机制,实现粘接区域的高效覆盖检测。针对试件个体差异引起的信号漂移问题,采用基于峰值比例阈值的相位对齐方法,通过优化窗口长度同步保留损伤敏感特征并抑制噪声干扰。进一步构建域自适应迁移学习网络(Domain-adaptive transfer learning,DATL),实现跨试件损伤特征的分布对齐。试验表明,在跨试件测试场景下,DATL模型准确率仅下降3.9%,域间分布差异指数从0.31降至0.10;在目标域数据量不足40%时,其准确率仍达85%,较卷积神经网络(Convolutional neural network,CNN)提升19.4%。该方法缓解了对损伤类型和试件一致性的依赖,可降低在役热防护结构脱粘检测的误报率与漏检率,为可重复使用飞行器的快速无损检测与健康评估提供了一种可行的解决参考方案。
文摘针对单相矩阵式无线电能传输MC-WPT(matrix converter based wireless power transfer)系统网侧电流谐波含量大的问题,提出1种谐波抑制调制策略,可有效降低网侧电流低次谐波含量及总谐波失真度THD(total harmonic distortion)。分析谐振槽电压电流特性,基于参数归一化方法得到2个基波分量的等效电路,进而推导出MC-WPT的数学模型。在此基础上,以消除低次谐波含量为目标,应用计算法得到接收侧H桥的优化调制波,使网侧电流低频成分仅有工频分量,从而降低网侧电流THD。最后搭建实验平台,验证所提谐波抑制调制策略的可行性与有效性。
文摘文中以非隔离型柔性互联配电网为研究对象,针对交流系统发生单相接地故障时,因零序分量传递特性导致的典型接地故障检测方法适应性问题开展研究。首先,建立非隔离型智能软开关(soft open point, SOP)的零序等值拓扑网络,提出零序分量的传递方程并定量分析零序分量传递至非故障侧的大小,分析不同场景下零序分量抑制效果;然后,分别对小电流互联系统、小电阻互联系统、小电流和小电阻互联系统的典型保护进行适应性分析,结果表明,在非隔离型柔性互联系统中,零序分量传递至系统健全侧后保护可能发生误动或误告警;最后,基于PSCAD建立典型非隔离型柔性互联配电网模型,对不同互联系统的保护适应性分析进行验证。文中研究结论可为非隔离型柔性互联配电网的保护配置提供理论支撑。
