Mechanical Systems and Signal Processing最新文献

An incremental kriging-assisted and EGO-based online model updating method for real-time hybrid simulation 基于kriging辅助的基于ego的实时混合仿真在线模型更新方法

IF 8.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2026-01-17 DOI: 10.1016/j.ymssp.2026.113890

Weipeng Zhong , Changle Peng , Weijie Xu , Cheng Chen

Real-time hybrid simulation with model updating (RTHSMU) enables online refinement of numerical substructures using experimentally measured data from rate-dependent physical substructures, therefore providing a more cost-effective and accurate means of replicating structural responses subjected to ground motions. However, the stringent computational speed requirements of real-time hybrid simulation present challenges for developing efficient model updating methods. Existing methods often focus on improving structural response accuracy but neglect accuracy of parameter identification. This study introduces an incremental Kriging-assisted and Efficient Global Optimization (EGO)-based online model updating method. The Kriging model approximates the error response surface of updated parameters, while its incremental formulation reduces computational complexity. The EGO algorithm identifies high-value candidate points to incrementally refine the Kriging model. Additionally, a transfer learning strategy leverages historical information from prior timesteps, reducing the need for new sample points required at each step. Experimental validation on a six-story steel moment-resisting frame equipped with self-centering viscous dampers demonstrates that the proposed method significantly enhances the structural response accuracy in RTHS while improving accuracy of parameter identification compared to existing approaches.

实时混合模拟与模型更新（RTHSMU）能够利用速率相关的物理子结构的实验测量数据在线改进数值子结构，因此提供了一种更经济、更准确的方法来复制受地面运动影响的结构响应。然而，实时混合仿真对计算速度的严格要求给开发高效的模型更新方法带来了挑战。现有的方法往往侧重于提高结构响应精度，而忽略了参数辨识的精度。提出了一种基于kriging辅助的高效全局优化（EGO）的增量模型在线更新方法。Kriging模型近似于参数更新后的误差响应面，而其增量公式降低了计算复杂度。EGO算法识别高价值的候选点，以逐步改进Kriging模型。此外，迁移学习策略利用以前时间步的历史信息，减少了每一步所需的新样本点的需求。在装有自定心粘性阻尼器的六层钢抗矩框架上进行的试验验证表明，与现有方法相比，该方法显著提高了RTHS结构响应精度，同时提高了参数辨识精度。

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引用次数: 0

An extension of successive Nonlinear Chirp Component Analysis for blind source separation with time-varying mixing matrix 时变混合矩阵盲源分离的逐次非线性啁啾分量分析的扩展

IF 8.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2026-01-17 DOI: 10.1016/j.ymssp.2026.113897

Xujun Peng, Zhiyu Shi, Pengfei Jin, Jinyan Li, Tingyu Xiao

In this paper, we extend Successive Nonlinear Chirp Analysis (SNCCA) into a method capable of effectively handling the blind source separation model with time-varying mixing matrix (TV-BSS), termed TV-SNCCA. TV-SNCCA assumes the source signals as nonlinear chirp signals, ensuring the algorithm effectively extracts non-stationary source signals. Based on the expression of the TV-BSS model, TV-SNCCA uses the bandwidth of the demodulated source signals as the optimization objective, with the constraint that the observed signals are linear combinations of the source signals. Distinct from SNCCA, the mixing matrix here is time-varying, which is represented as a 3-dimensional matrix after discretizing the optimization algorithm. Inspired by matching pursuit-like methods, TV-SNCCA employs the ADMM(Alternating Direction Method of Multipliers) algorithm to extract only one source signal and its corresponding time-varying mixing vector at a time. After extraction, the component of the extracted source signal is subtracted from each channel. It then determines whether to extract the next source signal based on whether the energy ratio between the residual signals and the observed signals falls below a preset threshold. Validation using TV-BSS and TV-UBSS examples demonstrates that TV-SNCCA can effectively handle BSS or underdetermined BSS models with varying mixing matrix. The time-varying mixing matrix, non-stationary signals and their instantaneous frequencies (IFs) are all accurately identified. Subsequent analyses verify the impact of different values of

N_{1}

and initial IFs on the method’s effectiveness and convergence. Finally, we apply our method to analyze response signals from time-varying vibration system including numerical simulations and experimental validations, successfully identifying the system’s time-varying natural frequencies and modal shapes from the response signals.

在本文中，我们将连续非线性啁啾分析（SNCCA）扩展为一种能够有效处理时变混合矩阵（TV-BSS）盲源分离模型的方法，称为TV-SNCCA。TV-SNCCA假设源信号为非线性啁啾信号，保证了算法有效提取非平稳源信号。基于TV-BSS模型的表达式，TV-SNCCA以解调后的源信号带宽为优化目标，约束观测信号为源信号的线性组合。与SNCCA不同的是，这里的混合矩阵是时变的，将优化算法离散化后表示为三维矩阵。TV-SNCCA受类匹配追踪方法的启发，采用ADMM（Alternating Direction Method of Multipliers）算法，每次只提取一个源信号及其对应的时变混合矢量。提取后，从每个通道中减去提取的源信号的分量。然后根据残差信号与观测信号之间的能量比是否低于预设阈值来决定是否提取下一个源信号。通过TV-BSS和TV-UBSS实例验证，TV-SNCCA可以有效地处理具有不同混合矩阵的BSS或待定BSS模型。时变混频矩阵、非平稳信号及其瞬时频率均能准确识别。随后的分析验证了不同N1值和初始if值对方法有效性和收敛性的影响。最后，将该方法应用于时变振动系统的响应信号分析，包括数值模拟和实验验证，成功地从响应信号中识别出系统的时变固有频率和模态振型。

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引用次数: 0

Nonlinear Stabilizing control for 7-DOF offshore cranes with velocity and friction estimation under complex wave-induced ship movements 基于速度和摩擦估计的复杂波浪船舶运动下七自由度海上起重机非线性稳定控制

IF 8.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2026-01-16 DOI: 10.1016/j.ymssp.2026.113889

Ling Yang , Xin Ma , Yining Yu , Lei Zhang

Complex marine environments, including persistent waves, ocean currents, and wind disturbances, present significant challenges to offshore crane operations. In this paper, a nonlinear stabilizing controller is proposed for 7-DOF offshore cranes to simultaneously achieve payload positioning and swing suppression under external disturbances. First, considering 7-DOF motions of the cranes, the ship’s heave, roll, and yaw motions, as well as wind disturbances and mechanical friction, an offshore crane model is developed using Lagrange’s modeling method. Additionally, a vector representing the ship’s motions is introduced for model transformation, thereby simplifying the original model. Then, based on the transformed model, an observer is designed to estimate the system state variables, which are employed to design auxiliary variables. To compensate for mechanical friction, wind disturbances, and actuator input dead zones, friction estimation terms and coupling terms are designed using the auxiliary variables, improving the transient performance of the control system. Additionally, saturated PD terms are designed to limit the controller’s output amplitude, enhancing the system safety. With the proposed controller, the payload can achieve precise positioning and effective swing suppression in complex marine environments and under the system’s uncertain dynamics. The stability of the control system is proven theoretically, and the self-built hardware platform demonstrates the performance of the proposed controller in terms of effectiveness, robustness, and anti-disturbance capability.

复杂的海洋环境，包括持续的海浪、洋流和风的干扰，给海上起重机的作业带来了巨大的挑战。针对七自由度海上起重机，提出了一种能同时实现载荷定位和外部扰动下摆动抑制的非线性稳定控制器。首先，考虑起重机的七自由度运动，船舶的升沉、横摇和偏航运动，以及风扰动和机械摩擦，利用拉格朗日建模方法建立了海上起重机模型。此外，还引入了表示船舶运动的矢量进行模型变换，从而简化了原模型。然后，基于变换后的模型设计观测器来估计系统状态变量，并利用状态变量来设计辅助变量。为了补偿机械摩擦、风干扰和执行器输入死区，利用辅助变量设计了摩擦估计项和耦合项，提高了控制系统的暂态性能。此外，饱和PD项的设计限制了控制器的输出幅度，提高了系统的安全性。在复杂的海洋环境和系统的不确定动力学条件下，有效载荷能够实现精确定位和有效的摆动抑制。从理论上证明了控制系统的稳定性，自制的硬件平台验证了所提控制器在有效性、鲁棒性和抗干扰能力方面的性能。

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引用次数: 0

Damage localization in bridges using curvature profiles identified from acceleration data via continuous wavelet transform 基于连续小波变换的加速度数据曲率曲线损伤定位方法

IF 8.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2026-01-16 DOI: 10.1016/j.ymssp.2026.113881

Sheng-Wang Zhang , Said Quqa , Antonio Palermo , Alessandro Marzani , Zhao-Hui Lu

Damage identification methods based on traffic-induced vibration data have gained significant attention in structural health monitoring of bridges, driven by the need for cost-effective sensing solutions. Recent studies have demonstrated that bridge curvature profiles can be identified from sparse acceleration measurements collected during vehicle passages using standard accelerometers. However, existing approaches for estimating curvature from acceleration data often struggle to suppress dynamic effects induced by moving vehicles. These methods typically rely on low-pass filters with a rigid cutoff threshold, which can compromise accuracy, especially during high-speed vehicle passages. To overcome this limitation, this study introduces a novel approach based on the continuous wavelet transform to isolate the quasi-static curvature profile and effectively remove dynamic components. The method is tested on a model that incorporates vehicle-bridge interaction effects and road roughness. Sensitivity analyses show that the proposed method outperforms standard filtering techniques across various sensor configurations, damage locations, severities, and multiple damage scenarios, even at relatively high vehicle speeds. Validation using field data further confirms the effectiveness and generality of the proposed approach.

由于需要具有成本效益的传感解决方案，基于交通诱发振动数据的损伤识别方法在桥梁结构健康监测中受到了极大的关注。最近的研究表明，使用标准加速度计可以从车辆通过时收集的稀疏加速度测量中识别桥梁曲率曲线。然而，现有的从加速度数据估计曲率的方法往往难以抑制由移动车辆引起的动态效应。这些方法通常依赖于具有严格截止阈值的低通滤波器，这可能会损害准确性，特别是在高速车辆通过时。为了克服这一局限性，本文提出了一种基于连续小波变换的方法来分离准静态曲率剖面，并有效地去除动态分量。在考虑车桥相互作用效应和路面粗糙度的模型上对该方法进行了验证。灵敏度分析表明，即使在相对较高的车速下，该方法在各种传感器配置、损伤位置、严重程度和多种损伤情况下也优于标准滤波技术。现场数据验证进一步证实了该方法的有效性和通用性。

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引用次数: 0

Analytical score matching for efficient stochastic response determination of nonlinear oscillators with parametric fractional dampers 带有参数分数阻尼器的非线性振子的有效随机响应分析分数匹配

IF 8.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2026-01-14 DOI: 10.1016/j.ymssp.2026.113874

Ketson R.M. dos Santos, João G.C.S. Duarte

Mechanical and structural systems subject to parametric excitations—fluctuations in mass, damping, or stiffness caused by phenomena such as fluid property variations or particle adhesion—are common in engineering applications. These excitations, whether deterministic or stochastic, can induce chaotic motion, instabilities, and stochastic resonance, compromising system reliability. Analyzing such systems is particularly challenging because external and parametric excitations must be addressed simultaneously, while fractional derivative terms modeling viscoelastic effects add further complexity to uncertainty propagation in nonlinear oscillators. This paper introduces an analytical score-matching methodology to evaluate the non-stationary probability density function (PDF) of the response amplitude of nonlinear oscillators equipped with a parametric fractional damper and subjected to white noise excitation. The method employs stochastic averaging to derive the stochastic differential equation governing the amplitude dynamics and reformulates the associated Fokker–Planck equation as a continuity equation. This formulation enables tracing amplitude evolution along equiprobability trajectories, thereby recovering the time-dependent PDF of the response amplitude. Numerical studies are performed for both linear and Duffing oscillators. The results reveal that the fractional derivative order significantly influences system dynamics by contributing simultaneously to damping and stiffness, which in turn shapes the response distribution. Comparisons with Monte Carlo simulations confirm the accuracy and computational efficiency of the proposed approach, demonstrating its potential as a robust tool for analyzing stochastic dynamical systems with combined parametric and fractional effects.

受参数激励的机械和结构系统——由流体性质变化或颗粒粘附等现象引起的质量、阻尼或刚度波动——在工程应用中很常见。这些激励，无论是确定性的还是随机的，都会引起混沌运动、不稳定和随机共振，从而影响系统的可靠性。分析这样的系统特别具有挑战性，因为必须同时处理外部和参数激励，而分数阶导数项建模粘弹性效应进一步增加了非线性振荡器中不确定性传播的复杂性。本文介绍了一种分析分数匹配方法，用于计算在白噪声激励下配置参数分数阻尼器的非线性振子响应幅值的非平稳概率密度函数。该方法采用随机平均导出控制振幅动力学的随机微分方程，并将相关的Fokker-Planck方程重新表述为连续性方程。该公式可以沿着等概率轨迹跟踪振幅演变，从而恢复响应振幅的随时间的PDF。对线性振荡器和杜芬振荡器进行了数值研究。结果表明，分数阶导数阶数通过同时影响阻尼和刚度来显著影响系统动力学，进而影响响应分布。与蒙特卡罗模拟的比较证实了所提出方法的准确性和计算效率，证明了它作为分析具有参数和分数效应的随机动力系统的强大工具的潜力。

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引用次数: 0

A data-driven framework for distributed dynamic load identification incorporating physics-based temporal causality constraints 一个数据驱动的分布式动态载荷识别框架，包含基于物理的时间因果约束

IF 8.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2026-01-14 DOI: 10.1016/j.ymssp.2026.113846

Rutong Chen, Jinhui Jiang, Yiyuan Guan

As the second inverse problem in structural dynamics, dynamic load identification is highly dependent on the system’s intrinsic properties. For distributed loads, establishing an accurate mapping between structural responses and the underlying dynamic excitations remains particularly challenging, and the ill-posed nature of the problem further amplifies measurement noise, leading to significant identification errors. To overcome these difficulties, this study proposes a novel distributed dynamic load identification framework based on a Transformer architecture that directly learns the inverse dynamic relationship without requiring explicit system parameter estimation. Specifically, Legendre orthogonal polynomial decomposition is first employed to transform the load identification task into the estimation of a finite set of orthogonal polynomial coefficients. Building upon this framework, innovative architectural optimizations are introduced by embedding physical constraints into attention computation and linear prediction, leveraging the temporal causality of dynamic responses. These enhancements improve model interpretability and substantially reduce training difficulty. Numerical simulations demonstrate that the proposed method can accurately identify sinusoidal, impact, and random loads under various noise levels. Furthermore, a distributed load identification experiment on a cantilever beam is carried out, validating the practical applicability of the approach. Finally, the selection of model hyperparameters is discussed based on fitting and generalization performance, and a comparative study with traditional dynamic calibration methods was conducted in an experimental setting, further demonstrating the superior accuracy, noise robustness, and practical reliability of the proposed framework.

作为结构动力学中的第二逆问题，动载荷识别高度依赖于系统的固有特性。对于分布式载荷，在结构响应和潜在动力激励之间建立精确的映射仍然是特别具有挑战性的，而且问题的病态性质进一步放大了测量噪声，导致显著的识别误差。为了克服这些困难，本研究提出了一种基于Transformer架构的分布式动态负载识别框架，该框架可以直接学习逆动态关系，而不需要显式的系统参数估计。具体而言，首先采用勒让德正交多项式分解将负荷识别任务转化为有限正交多项式系数集的估计。在此框架的基础上，通过将物理约束嵌入到注意力计算和线性预测中，利用动态响应的时间因果关系，引入了创新的架构优化。这些增强提高了模型的可解释性，并大大降低了训练难度。数值仿真结果表明，该方法能准确识别各种噪声水平下的正弦载荷、冲击载荷和随机载荷。最后，对某悬臂梁进行了分布式荷载识别实验，验证了该方法的实用性。最后，基于拟合和泛化性能讨论了模型超参数的选择，并在实验环境中与传统的动态校准方法进行了比较研究，进一步证明了该框架具有优越的精度、噪声鲁棒性和实用可靠性。

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引用次数: 0

Preliminary results of a fiber optic scour sensor (FOSS) for bridges 桥梁用光纤冲刷传感器（FOSS）初步研究结果

IF 8.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2026-01-14 DOI: 10.1016/j.ymssp.2026.113868

Kristopher Campbell , Maria Pregnolato , Raj Kamal Arora , Su Taylor , Remco Nieuwland , Piet van Andel , Myra Lydon

Bridges are a vital part of the infrastructure that shapes our society. The management of these assets against ever increasing climatic changes is providing unprecedented challenges for bridge asset owners worldwide. The effects of more frequent and severe rainfall flood events in the UK have exacerbated concerns around the management of bridge scour events. This research presents the development and field deployment of a Fiber Optic Scour Sensor (FOSS), designed to remotely monitor scour and infilling in real-time. This sensor consists of three sensing elements (fins) buried at different depths. As scouring occurs, the fins are exposed and free to move and register a response. Following the flood event, as the scour hole begins to infill, these fins are buried, and this process can be picked up on the data trace. A prototype FOSS was installed at Regent bridge in Northern Ireland; a site selected for its accessibility and suitability for monitoring. This paper outlines the installation, and the initial findings, following two storms in October 2023, demonstrating the sensor’s potential for real-time scour detection in operational environments.

桥梁是塑造我们社会的基础设施的重要组成部分。应对日益加剧的气候变化，这些资产的管理为全球桥梁资产所有者提供了前所未有的挑战。在英国，更频繁和严重的降雨洪水事件的影响加剧了人们对桥梁冲刷事件管理的担忧。本研究介绍了光纤冲刷传感器（FOSS）的开发和现场部署，旨在远程监控冲刷和实时填充。该传感器由埋在不同深度的三个传感元件（鳍）组成。当冲刷发生时，鱼鳍暴露在外，可以自由移动并做出反应。在洪水事件之后，随着冲刷孔开始被填满，这些鳍片被掩埋，这个过程可以在数据痕迹上发现。自由/开源软件的原型安装在北爱尔兰的Regent桥；根据其可达性和监测适用性而选择的站点。本文概述了2023年10月两次风暴后的安装情况和初步发现，展示了该传感器在作战环境中实时冲刷检测的潜力。

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引用次数: 0

Simulation and interpretable learning co-driven framework for multi-objective seismic monitoring of substation equipment 变电站设备多目标地震监测仿真与可解释学习协同驱动框架

IF 8.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2026-01-14 DOI: 10.1016/j.ymssp.2026.113876

Wang Zhu , Fabrizio Paolacci , Gianluca Quinci , Qiang Xie

Electrical equipment in substations subjected to earthquakes typically exhibits brittle damage at multiple vulnerable sections, but the exact positions on the sections are unpredictable. Relevant standards and research raise the importance of the stress response levels in seismic assessment. However, monitoring all strains at the vulnerable sections necessitates lots of strain sensors for each equipment, which is impractical because of the extensive quantity of equipment in a substation, and the strong electromagnetic interference induced by the equipment. Therefore, this paper proposes a simulation and learning co-driven prediction framework to identify multi-objective monitoring schemes. It develops multiple machine learning (ML) models to predict peak stress at multiple vulnerable sections by inputting easily-monitored responses (MRs). In which, the simulation model is cooperated to acquire precise response data, addressing the scarcity of actual samples due to the absence of monitoring systems and the limited number of earthquakes. Then, it ranks the importance of MRs for each ML model using the Shapley additive explanation method, and combines the important MRs of various ML models through the proposed Intersection, Union, or Stack strategies. The combined MRs facilitate the reconstruction of ML models, which are subsequently implemented at the site to monitor responses for post-earthquake efficient predictions. A case study on a high-voltage transformer bushing is performed. Shaking table tests validate the efficacy of the obtained monitoring schemes in both intact and damaged scenarios, revealing the practicality of applying the proposed framework to efficiently identify damage to substation equipment after earthquakes.

受地震影响的变电站的电气设备通常在多个脆弱部分出现脆性损坏，但这些部分的确切位置是不可预测的。相关标准和研究提高了应力响应等级在地震评价中的重要性。然而，由于变电站中设备数量众多，且设备产生的电磁干扰较强，因此监测脆弱段的所有应变需要为每台设备配备大量应变传感器，这是不现实的。因此，本文提出了一种模拟和学习共同驱动的预测框架来识别多目标监测方案。它开发了多个机器学习（ML）模型，通过输入易于监测的响应（MRs）来预测多个脆弱部分的峰值应力。其中，模拟模型配合获得精确的响应数据，解决了由于缺乏监测系统和地震数量有限而导致实际样本稀缺的问题。然后，使用Shapley加性解释方法对每个ML模型的MRs重要性进行排序，并通过提出的交集、联合或堆栈策略将各种ML模型的MRs进行组合。结合MRs有助于ML模型的重建，这些模型随后在现场实施，以监测震后有效预测的响应。对高压变压器套管进行了实例研究。振动台试验验证了所获得的监测方案在完整和损坏情况下的有效性，揭示了应用所提出的框架有效识别地震后变电站设备损坏的实用性。

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引用次数: 0

Multi-mode flexural guided waves imaging in pipes 管道中多模弯曲导波成像

IF 8.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2026-01-14 DOI: 10.1016/j.ymssp.2026.113885

Zhao Wang , Junkai Tong , Xiao Ying , He Sun , Lei Qi , Haoran Jin , Mengying Xie , Yang Liu

Guided wave tomography is a promising technique for quantitative evaluation of pipe defects, but its in-service application has long been constrained by the inherent limited-view imposed by typical transducer layouts, leading to low resolution and severe artifacts. This study proposes a novel imaging method based on multi-mode flexural guided waves. By exploiting the helical propagation characteristics of flexural modes with different circumferential orders, a larger synthetic angular coverage of virtual rays is achieved, overcoming the detection limitations of conventional axial paths. A multi-mode physics-informed neural network is developed, which decouples and reconstructs mixed-mode guided wave signals in parallel branches and embeds dispersion equations as a physical interpreter to supervise inversion consistency and realize multi-source information fusion. Datasets containing randomized defects are generated by a finite difference forward operator. Numerical simulations demonstrate that the proposed method can accurately reconstruct various defect types, achieving an average Pearson correlation coefficient of 0.9244 on an independent test set. Comparative analyses against single mode imaging are conducted, and imaging performance is further evaluated under different defect sizes, eccentricity, and noise levels. In a real pipe experiment, the reconstructed result achieves a correlation of 0.9068 with the ground truth, and the relative error in maximum wall loss prediction is only 4.5%. The proposed method deeply integrates physical mechanisms with data driven framework to address the limited-view imaging challenge in pipes, demonstrating strong potential for engineering applications.

导波层析成像技术是一种很有前途的管道缺陷定量评估技术，但其在实际应用中一直受到典型换能器布局固有的有限视野的限制，导致分辨率低和严重的伪影。本文提出了一种基于多模弯曲导波的成像方法。利用不同周向阶弯曲模态的螺旋传播特性，克服了传统轴向路径检测的局限性，实现了更大的虚拟射线合成角覆盖。提出了一种多模物理信息神经网络，该网络对并联支路的混合模导波信号进行解耦和重构，并嵌入色散方程作为物理解释器来监督反演一致性，实现多源信息融合。包含随机缺陷的数据集由有限差分正演算子生成。数值模拟结果表明，该方法可以准确地重建各种缺陷类型，在独立测试集上的平均Pearson相关系数为0.9244。与单模成像进行了对比分析，并进一步评估了不同缺陷尺寸、偏心率和噪声水平下的成像性能。在实际管道实验中，重构结果与地面真值的相关性为0.9068，最大壁损预测的相对误差仅为4.5%。该方法将物理机制与数据驱动框架深度集成，解决了管道中有限视点成像的挑战，显示出强大的工程应用潜力。

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引用次数: 0

An efficient decoupling-based multi-harmonic hybrid control for helicopter active vibration suppression 基于解耦的直升机主动减振多谐混合控制

IF 8.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2026-01-13 DOI: 10.1016/j.ymssp.2026.113873

Jiahou Zhao , Wanqiang Liu , Hongwu Li , Xinhua Long

The multi-harmonic vibration response, with the blade-passing frequency as the fundamental harmonic, is the primary target in helicopter vibration control. Algorithms based on the filtered-x least mean square (FxLMS) framework typically struggle to balance control performance and computational efficiency in multi-harmonic scenarios. To enhance control effectiveness while reducing computational cost, a decoupling-based multi-harmonic hybrid control (DMHHC) algorithm is proposed. A novel decoupling compensator is designed to achieve secondary-path decoupling and amplitude equalization of the filtered reference signals across frequency bands, allowing a single FxLMS to efficiently control multiple harmonics and thus significantly reduce computational cost. Furthermore, a multi-harmonic hybrid control framework is established by integrating repetitive control (RC) with FxLMS. The secondary-path decoupling effectively eliminates the interference between RC and FxLMS during integration, enabling the algorithm to combine the fast convergence of RC with the steady-state accuracy of FxLMS. Both simulations and experiments verify the effectiveness of the proposed DMHHC algorithm, demonstrating its potential as a practical engineering solution for helicopter vibration suppression.

以过叶频率为基频的多谐振动响应是直升机振动控制的主要目标。基于滤波-x最小均方（FxLMS）框架的算法通常难以在多谐波场景下平衡控制性能和计算效率。为了在提高控制效果的同时降低计算量，提出了一种基于解耦的多谐波混合控制算法。设计了一种新型的解耦补偿器，实现了滤波后参考信号跨频带的二次路径解耦和幅度均衡，使单个FxLMS能够有效地控制多个谐波，从而显著降低计算成本。在此基础上，将重复控制与FxLMS相结合，建立了多谐混合控制框架。二次路径解耦有效地消除了积分过程中RC与FxLMS之间的干扰，使算法能够将RC的快速收敛性与FxLMS的稳态精度相结合。仿真和实验验证了所提出的DMHHC算法的有效性，显示了其作为直升机振动抑制实际工程解决方案的潜力。

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引用次数: 0