Mechanical Systems and Signal Processing最新文献

{"title":"Joint space–time wind field data extrapolation and uncertainty quantification using nonparametric Bayesian dictionary learning","authors":"George D. Pasparakis ,&nbsp;Ioannis A. Kougioumtzoglou ,&nbsp;Michael D. Shields","doi":"10.1016/j.ymssp.2025.113324","DOIUrl":"10.1016/j.ymssp.2025.113324","url":null,"abstract":"<div><div>Wind velocity/pressure measurements, whether in the field or a wind tunnel, are typically limited to a small number of sensor locations, which prohibits high resolution of the spatio-temporal velocity/pressure field. A methodology is developed, based on nonparametric Bayesian dictionary learning, for joint space–time wind field data extrapolation and estimation of related statistics by relying on limited/incomplete measurements. Specifically, utilizing sparse/incomplete measured data, a time-dependent optimization problem is formulated for determining the expansion coefficients of an associated low-dimensional representation of the stochastic wind field. Compared to an alternative, standard, compressive sampling treatment of the problem, the developed methodology exhibits the following advantages. First, the Bayesian formulation enables also the quantification of the uncertainty in the estimates. Second, the requirement in standard CS-based applications for an a priori selection of the expansion basis is circumvented. Instead, this is done herein in an adaptive manner based on the acquired data. Overall, the methodology exhibits enhanced extrapolation accuracy, even in cases of high-dimensional data of arbitrary form, and of relatively large extrapolation distances. Thus, it can be used, potentially, in a wide range of wind engineering applications where various constraints dictate the use of a limited number of sensors. The efficacy of the methodology is demonstrated by considering two case studies. The first relates to the extrapolation of simulated wind velocity records consistent with a prescribed joint wavenumber-frequency power spectral density in a three-dimensional domain (2D and time). The second pertains to the extrapolation of four-dimensional (3D and time) boundary layer wind tunnel experimental data that exhibit significant spatial variability and non-Gaussian characteristics.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"239 ","pages":"Article 113324"},"PeriodicalIF":8.9,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The method for training dataset forming recorded by analog sensors to determine the helicopter turboshaft engines efficiency","authors":"Denys Baranovskyi ,&nbsp;Serhii Vladov ,&nbsp;Maryna Bulakh ,&nbsp;Valerii Sokurenko ,&nbsp;Oleksandr Muzychuk ,&nbsp;Victoria Vysotska","doi":"10.1016/j.ymssp.2025.113368","DOIUrl":"10.1016/j.ymssp.2025.113368","url":null,"abstract":"<div><div>This article presents a novel approach to intelligent monitoring and control of complex dynamic systems, focusing specifically on helicopter turboshaft engines during flight. The developed method includes multi-channel signal processing, adaptive discretization and quantization, temporal feature extraction, and singular spectrum analysis. The key components are median, mean, and Hilbert filtering to eliminate noise, as well as adaptive quantization and clustering (hierarchical, DBSCAN, Gaussian mixtures) to ensure homogeneity and representativeness of samples. The method was verified using a neural network model, demonstrating a mean square error (MSE) of no more than 0.025 on training, validation, and test data. As a numerical experiment part, the TV3-117 engine compressor’s efficiency installed on the Mi-8MTV helicopter was calculated. The results showed a maximum MSE deviation from the reference value of no more than 0.862%, which confirms the developed method’s high accuracy. The article also proves the theorem on homogeneity and representativeness of data, according to which, if the training and test samples satisfy the homogeneity criteria (according to the Fisher-Pearson and Fisher-Snedecor statistical criteria) and representativeness (according to cluster analysis), they can be considered suitable for use in practical problems of modeling, classification, and forecasting. This theorem’s theoretical justification confirms the need for strict quality control of samples before training models. Scenarios with artificial introduction of errors into the data were simulated, which led to calculations and confirmed the instability and importance of ensuring homogeneity and representativeness of datasets. The developed method allows for a significant increase in the accuracy of predicting and diagnosing anomalies in the helicopter turboshaft engine’s operation, providing a reliable basis for intelligent monitoring and control in real operating conditions.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"239 ","pages":"Article 113368"},"PeriodicalIF":8.9,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uncertainty quantification for the modal shape sensing of structures undergoing geometrically non-linear deformation","authors":"Janto Gundlach ,&nbsp;Marc Böswald ,&nbsp;Jurij Sodja","doi":"10.1016/j.ymssp.2025.113249","DOIUrl":"10.1016/j.ymssp.2025.113249","url":null,"abstract":"<div><div>Shape sensing techniques allow for the time-efficient reconstruction of displacements based on measured strain data. There are technical applications, where the structure of interest is deformed in the geometrically non-linear domain. In aeronautics, this is the case for high-aspect-ratio wings, which are more frequently found in future designs. Only shape sensing methods that specifically take the non-linearity into account, can deliver appropriate displacement estimates for such application. A shape sensing method based on the linear modal approach can be utilised incrementally to capture the geometric non-linearity; it has therefore been denoted incremental modal method (IMM). This paper presents analytical relations for the uncertainty propagation for the various input quantities of the method, specifically strain mode shapes, displacement mode shapes, and measured strain. Deterministic shape sensing and uncertainty propagation are demonstrated using data obtained with a finite element model of a high-aspect-ratio wing experiencing geometric non-linear deflections in flapwise bending. Virtual strain and acceleration sensors are assumed for this setup, imitating the instrumentation conceivable for experimental work. The results obtained by analytical propagation are compared to Monte Carlo simulations for the purpose of validation. The derived propagation formulas make it possible to follow the evolution of the uncertainties over the number of increments. Given that the variability of the input quantities is known, the number of increments that minimise uncertainties can be determined for a model-free application of the shape sensing. Together with the deterministic estimates provided by an FE model, it is possible to determine the ideal number of increments for a specific shape sensing application in the geometrically non-linear domain.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"239 ","pages":"Article 113249"},"PeriodicalIF":8.9,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel ring piezoelectric vibration isolator for wideband vibration control of underwater vehicles: Concept, analysis and verification","authors":"Ziyu Shen ,&nbsp;Liang Wang ,&nbsp;Rui Qi ,&nbsp;Xiaoming Geng ,&nbsp;Haoren Feng ,&nbsp;Chunsheng Zhao","doi":"10.1016/j.ymssp.2025.113344","DOIUrl":"10.1016/j.ymssp.2025.113344","url":null,"abstract":"<div><div>Underwater vehicles (UUVs) are essential for marine defenses, while noise and vibration disturbances frequently jeopardize their stability and stealth. To meet the high-precision, high-efficiency, wideband and multidirectional vibration control requirements in the small propulsion compartment of UUVs, a novel ring active vibration isolator with frequency-segmented gain control is proposed in this study. Firstly, the structure of the vibration isolator based on piezoelectric actuators is designed to meet radial bearing and vibration isolation simultaneously. Then, a mathematical model of the ring active vibration isolator including the piezoelectric actuator dynamics is developed, and the segmented active control method (focusing on segmented control gain) for wideband disturbances is proposed to overcome the difficulties of effective wideband control. Finally, the prototype is manufactured and assembled to verify the efficiency of the ring piezoelectric vibration isolator in controlling arbitrary radial disturbances, and the wideband vibration control experiments are used to explore the feasibility of the segmented vibration control method. The results show that, for unidirectional disturbances (single radial direction), the greatest amplitude attenuation reaches 91 % at resonant frequencies, and the control performance is also excellent in non-resonant frequencies with residual disturbance as low as 0.03 g. Wideband disturbances coupled in the rotational direction (combined <em>x</em> and <em>y</em> radial directions) are effectively controlled, achieving 88 % (<em>x</em>) and 48 % (<em>y</em>) reductions. This study on the ring piezoelectric vibration isolator with the segmented vibration control method can be used as a reference for wideband vibration control of UUVs.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"239 ","pages":"Article 113344"},"PeriodicalIF":8.9,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hammerstein structure based high-precision modeling and identification of piezoelectric fast steering mirror","authors":"Sen Yang ,&nbsp;Xiaofeng Li ,&nbsp;Yanan Li","doi":"10.1016/j.ymssp.2025.113329","DOIUrl":"10.1016/j.ymssp.2025.113329","url":null,"abstract":"<div><div>Research on the hysteretic-coupling between dual piezoelectric actuators under uniaxial condition and electromechanical cross-coupling under biaxial condition of the complex piezoelectric fast steering mirror (PFSM) system remains insufficiently explored, resulting in persistent challenges to achieving high-precision modeling. In this paper, a comprehensive model of the PFSM is established based on the Hammerstein structure. An improved asymmetric Bouc–Wen model is proposed to characterize the nonlinear rate-independent hysteresis, while a biaxial coupling dynamic is derived to represent the linear rate-dependent physical behavior. Considering the isolation of each module across different frequency scales, a step-by-step parameter identification method is presented. Experimental results show that the output of the identified model exhibits excellent consistency with the hysteresis, creep, and electromechanical behaviors of the PFSM. Finally, the predicted outputs are compared with those of existing comprehensive models and evaluated against measured data under various excitation signals. The significant reduction in errors validates the effectiveness of the proposed modeling approach.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"239 ","pages":"Article 113329"},"PeriodicalIF":8.9,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Finite-time tracking control for the ball and beam system based on a new fast terminal decoupled sliding mode control in the presence of matched and mismatched uncertainties","authors":"Abdollah Hasan Nezhad ,&nbsp;Mohammad Reza Soltanpour ,&nbsp;Saeed Zaare","doi":"10.1016/j.ymssp.2025.113283","DOIUrl":"10.1016/j.ymssp.2025.113283","url":null,"abstract":"<div><div>This paper presents a novel decoupled sliding mode controller for finite-time position tracking in ball-and-beam systems in the presence of matched and mismatched uncertainties. The proposed controller employs two fast terminal sliding surfaces and a novel coupling variable to ensure rapid and simultaneous convergence of all sliding surfaces to zero. A new reaching law is introduced to minimize chattering while ensuring finite-time asymptotic stability. Additionally, a finite-time extended state observer is employed to estimate disturbances and system states within a finite time frame, without requiring prior knowledge of uncertainty bounds. Furthermore, the finite-time convergence stability of the closed-loop system is proved in the Lyapunov framework. The control signal design is simplified, as it requires knowledge of only a small known portion of the system dynamics rather than the entire dynamics. The proposed method is validated through simulations and hardware-in-the-loop experiments, demonstrating enhanced robustness, faster convergence, and significantly reduced chattering compared to existing approaches.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"239 ","pages":"Article 113283"},"PeriodicalIF":8.9,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bayesian model inference with complex posteriors: Exponential-impact-informed Bayesian Quadrature","authors":"Pengfei Wei","doi":"10.1016/j.ymssp.2025.113333","DOIUrl":"10.1016/j.ymssp.2025.113333","url":null,"abstract":"<div><div>Estimation of multimodal and sharp posteriors with nonlinear dependencies as well as the associated model evidence remains a critical challenge in many Bayesian model inference tasks such as model parameter calibration, model selection and model averaging. Bayesian Quadrature (BQ) based on approximating the logarithm of likelihood with a Gaussian Process surrogate model has been proven to be a promising scheme for multimodal inference, but the mechanism behind it has not yet been sufficiently investigated. By exploring the mechanism of exponential impact behind this, I first answer the questions “why it works?”, as well as “can it work better, and how?” This mechanism then motivates the development of a simpler but more effective BQ method informed by the exponential impact. This BQ method is equipped with measures of prediction uncertainties and active learning, driven by two new acquisition functions, which have insightful interpretations, closed-form expressions and sound performance. Further, a transitional learning scheme based on adaptive tempering is developed and embedded into the developed BQ method, allowing for adaptive inference of sharp posteriors with desired accuracy. Several specific treatments, including elimination of error accumulation across stages, adaptive specification of tempering parameters, etc., have been developed for achieving the robust and efficient Transitional Bayesian Quadrature (TBQ) algorithm. Ultimately, the performance of TBQ for learning posteriors with multiple disconnected modes, high sharpness and nonlinear dependencies are demonstrated with both numerical cases and dynamics models.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"239 ","pages":"Article 113333"},"PeriodicalIF":8.9,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of railway bridge modal properties based solely on acceleration data from traversing trains","authors":"Charikleia D. Stoura ,&nbsp;Szymon Greś ,&nbsp;Vasilis K. Dertimanis ,&nbsp;Lucian Ancu ,&nbsp;Eleni N. Chatzi","doi":"10.1016/j.ymssp.2025.113342","DOIUrl":"10.1016/j.ymssp.2025.113342","url":null,"abstract":"<div><div>Railway bridges are vital components of rail infrastructure, yet many are aging and require effective monitoring. Traditional Structural Health Monitoring (SHM) methods, while accurate, are often costly and impractical for large-scale deployment. This study proposes a novel indirect monitoring approach to identify bridge eigenfrequencies using only acceleration data from trains. Leveraging vehicle–bridge interaction, the method proposes a two-step identification framework. First, a Bayesian filter is employed to estimate the unknown vehicle states and contact forces, removing the need for direct force and vehicle states measurements, which is commonly assumed as a prerequisite in previous works. Second, the estimated states and contact forces are used to define the inputs and outputs in the identification of the bridge modal properties. To this end, this study examines two identification approaches: an input/output, covariance-driven subspace identification (IO-COV) algorithm and an Auto-Regressive Moving Average with eXogenous input (ARMAX) method. The considered IO-COV approach additionally includes an uncertainty quantification step, used to filter out spurious frequency estimates. The approach is validated through numerical simulations. More importantly, the proposed methodology is verified on data collected via the Swiss Federal Railways diagnostic vehicle from an operational bridge structure, namely the Aarebrücke bridge in Uttigen, Switzerland. The identified frequencies align well with reference values, confirming the feasibility of indirect methods for accurate and cost-efficient bridge monitoring. The study addresses key challenges such as unknown inputs and high vehicle speeds, while also outlining remaining limitations and future directions.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"239 ","pages":"Article 113342"},"PeriodicalIF":8.9,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unsupervised domain adaptation method for bearing fault diagnosis assisted by twin data under extreme sample scarcity","authors":"Zhihui Men ,&nbsp;Dao Gong ,&nbsp;Kai Zhou ,&nbsp;Yuejian Chen ,&nbsp;Jinsong Zhou","doi":"10.1016/j.ymssp.2025.113359","DOIUrl":"10.1016/j.ymssp.2025.113359","url":null,"abstract":"<div><div>In small-sample bearing fault diagnosis, synthetic signals generated by simulation or generative models are commonly used to augment datasets. However, such signals often lack realistic noise and nonlinear characteristics, resulting in a domain gap between synthetic and real data. To address this, we propose an end-to-end method based on style transfer to generate twin data that better resembles real-world signals. First, a finite element model is built to derive the relationship between contact stiffness and radial force, and dynamic simulations are conducted using RecurDyn to obtain initial signals. Then, an Adaptive Style Transfer Network (AdasTNet) is employed to transfer the “style” of real signals to the simulated ones, enhancing their similarity in both time and frequency domains. The resulting twin data serves as the source domain, while the real data—without any labels—is treated as the target domain. We perform unsupervised domain adaptation using a CNN backbone combined with domain adversarial training and Maximum Mean Discrepancy (MMD) minimization. Experimental results show that the proposed method outperforms conventional GAN-based approaches in both accuracy and stability. Moreover, the model is lightweight and efficient, making it well-suited for real-world deployment in data-scarce scenarios.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"239 ","pages":"Article 113359"},"PeriodicalIF":8.9,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel compound fault diagnosis for rolling bearing based on sparse harmonic feature mode decomposition and enhanced spectral amplitude modulation","authors":"Weiliang Sun,&nbsp;Zong Meng,&nbsp;Jingbo Liu,&nbsp;Dengyun Sun,&nbsp;Kai Chen,&nbsp;Yonglei Ren","doi":"10.1016/j.ymssp.2025.113343","DOIUrl":"10.1016/j.ymssp.2025.113343","url":null,"abstract":"<div><div>To effectively tackle the challenge of accurately extracting compound fault features from rolling bearing vibration signals, a novel method termed sparse harmonic feature mode decomposition and enhanced spectral amplitude modulation is proposed. The method combines the superior mode extraction capability of feature mode decomposition with the nonlinear feature identification advantage of spectral amplitude modulation. First, a sparsity factor is introduced to refine the output signal of a finite impulse response filter, enhancing the sparsity of the signal. Second, the filter coefficients are optimized with the envelope harmonic noise ratio as the objective function, which facilitates the extraction of essential feature components. Then, the extracted components undergo nonlinear frequency and amplitude modulation. The spectral coherence of the modulate modal signals is calculated to capture modulation characteristics. Finally, an enhanced envelope spectrum strategy is adopted to improve the accuracy of fault feature identification. Results from both simulations and experimentals confirm that the SHFMD-ESAM method can accurately separate and identify multiple compound fault features in rolling bearings. Compared with existing methods, it achieves higher accuracy and robustness, demonstrating strong potential for rolling bearing fault diagnosis.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"239 ","pages":"Article 113343"},"PeriodicalIF":8.9,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}