Open research questions in Structural Health Monitoring Techniques

What the literature leaves open

• The lack of sensitive, direct mechanical monitoring techniques for fault slip rates. The need for accurate detection of fault slip rates to predict instability hazards.

  Monitoring Structural Plane Slip Using Bolt Axial Force: Insights from Accelerated Shear Experiments · 2026 · DOI

• The need to develop a monitoring method that can detect scour-related structural changes before visible damage or collapse occurs. The challenge of selecting the most relevant features for classifier training and evaluation.

  Leveraging Bridge Scour Detection by Multi-Model Machine Learning and Drive-By Data · 2026 · DOI

• It notes the need to ensure the reliability and accuracy of the sensor measurements. The paper highlights the challenge of providing a cost-effective and energy-efficient solution for long-term infrastructure resilience.

  Wireless Accelerometer Architecture for Bridge SHM: From Sensor Design to System Deployment · 2025 · DOI

• Existing models do not account for non-linear interfacial effects. The need for a realistic model that can predict the dynamic response of delaminated composite beams.

  Time Response of Delaminated Active Sensory Composite Beams Assuming Non-Linear Interfacial Effects · 2025 · DOI

• Conventional inspection and monitoring methods do not meet the growing needs due to the size and complexity of composite structures. Physics-based approaches are frequently constrained by high computational costs and the need for accurate material parameters.

  An Overview of Damage Identification in Composite Structures—From Computational Methods to Machine Learning · 2025 · DOI

• The limitation of using low-cost cameras with limited resolution and FPS rate. The need to estimate terracotta thickness, Young's modulus, and density without direct measurement.

  Dynamic Identification of the Sarcophagus of the Spouses by Means of Digital Video Analysis · 2025 · DOI

• The lack of a non-contact method to identify the dynamic behavior of fragile museum objects. The need for a technique to validate the dynamic identification of the Sarcophagus.

  Dynamic Identification of the Sarcophagus of the Spouses by Means of Digital Video Analysis · 2025 · DOI

• Results show that low-intensity excitation (EQ1) provides insufficient information to uniquely constrain material and damping parameters, often leading to bound-driven or compensatory parameter interactions associated with low identifiability and yielding deceptively good fits with non-physical parameter estimates.

  Bayesian nonlinear finite element model updating of a full-scale reinforced-concrete bridge column under low-to-moderate seismic excitation · 2026 · DOI

• Further investigation on the optimum hyperparameters for SMIDA and the SMIDA-applicable range is needed to further validate the mentioned relationship.

  Leveraging finite element model with transfer learning for data-driven-based structural damage identification · 2026 · DOI

• The study aims to address the lack of comprehensive analysis of the temperature-induced effects on double-ribbed plate girders in cable-stayed bridges.

  HEALTH‑MONITORING‑BASED INVESTIGATION OF THERMAL EFFECTS ON DOUBLE‑RIBBED PLATE GIRDERS OF CABLE‑STAYED BRIDGES · 2026 · DOI

• Further validation of LiDAR under field and dynamic loading conditions is needed. Evaluation of LiDAR for measuring other structural health parameters, such as strain and acceleration.

  Full field LiDAR-based measurement of deflection and support condition effects in a scaled bridge model: comparison with traditional point sensors · 2026 · DOI

• Traditional SHM methods may not capture the full extent of structural behavior. There is a need for noncontact techniques that can capture changes in deformation patterns across support-condition cases.

  Full field LiDAR-based measurement of deflection and support condition effects in a scaled bridge model: comparison with traditional point sensors · 2026 · DOI

• Traditional methods for damage detection have limitations, such as requiring access to all parts of the structure. There is a need for a new approach that can detect damage with high accuracy and prioritize maintenance.

  A Hybrid Experimental-Numerical Approach for Structural Health Monitoring Using Sem and Measured FRF · 2026 · DOI

• The acceleration parameters were determined based on observations from earlier constant-rate shear studies. The study only obtained data limited to the fracture state of the rock and bolt, the displacement field of the rock surface, the axial force in the bolt, and the post-test condition.

  Monitoring Structural Plane Slip Using Bolt Axial Force: Insights from Accelerated Shear Experiments · 2026 · DOI

• There is no suitable theoretical method for estimating structural damping at the design stage. The modal damping ratio of a completed or under-construction bridge can only be obtained through field dynamic tests.

  Review of Bridge Structure Damping Model and Identification Method · 2024 · DOI

• The dynamic characterization of structures using discrete models, as well as the application of modal superposition to compute their dynamic response, has been rarely explored in the literature.

  Modal analysis and superposition for dynamic response of structures with discontinuities using HybriDFEM · 2025 · DOI

• To investigate the effect of noise contamination on the method. To develop a more robust approach that can handle complex structures and various types of damage.

  A Hybrid Experimental-Numerical Approach for Structural Health Monitoring Using Sem and Measured FRF · 2026 · DOI

• To investigate the effect of noise on the proposed method. To compare the proposed method with other methods.

  Nonlinear damping identification using an extended stabilized layers method · 2026 · DOI

• The study is a simulation-based investigation, - The framework has not been validated in the field, - The analysis is limited to bridge-level detection and does not consider support-level…

  Leveraging Bridge Scour Detection by Multi-Model Machine Learning and Drive-By Data · 2026 · DOI

• The study only considers a simply-supported steel beam and a continuous beam bridge, - The study uses a limited number of measurement points, - The study does not consider other types of damage or complex damage…

  Generalized Local Curvature Modal Information Entropy (GLCME) for Mitigating Nodal Blindness in Beam Damage Assessment · 2026 · DOI

• Further evaluation of Lock-in filtering for characterizing subtle periodic mechanical behaviors, - Investigation of the application of the novel approach to other composite…

  Low Poisson’s Ratio Measurement on Composites Based on DIC and Frequency Analysis on Tensile Tests · 2025 · DOI

• Traditional methods often struggle with low strain measurements and non-uniform strain distributions inherent in these anisotropic materials. The development of predictive models or mechanical simulations for woven composite materials represents a significant scientific challenge for the practical design of efficient parts.

  Low Poisson’s Ratio Measurement on Composites Based on DIC and Frequency Analysis on Tensile Tests · 2025 · DOI

• Advancing bridge structural damping theory and identification methods - Developing new damping identification techniques - Improving the accuracy of modal damping ratio…

  Review of Bridge Structure Damping Model and Identification Method · 2024 · DOI

• High computational costs - Need for accurate material parameters - Challenges in considering environmental and operational…

  An Overview of Damage Identification in Composite Structures—From Computational Methods to Machine Learning · 2025 · DOI

• Interpretable, uncertainty-aware ML. Integrate calibrated probabilities, conformal prediction, and DT-consistency checks to produce explanations and reliable risk bounds for operators and regulators. Standardized benchmarks.

  Field-Validated Digital Twin–Enabled Structural Health Monitoring for Offshore High-Pile Wharves · 2026 · DOI

Most-cited papers in Structural Health Monitoring Techniques

• A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications · Mechanical Systems and Signal Processing · 2020 · 1,423 citations
• A review of computer vision–based structural health monitoring at local and global levels · Structural Health Monitoring · 2020 · 776 citations
• Data-Driven Structural Health Monitoring and Damage Detection through Deep Learning: State-of-the-Art Review · Sensors · 2020 · 764 citations
• Review of Bridge Structural Health Monitoring Aided by Big Data and Artificial Intelligence: From Condition Assessment to Damage Detection · Journal of Structural Engineering · 2020 · 682 citations
• Review on the new development of vibration-based damage identification for civil engineering structures: 2010–2019 · Journal of Sound and Vibration · 2020 · 616 citations
• A Model-Driven Scheme to Compensate the Strain-Based Non-Intrusive Dynamic Pressure Measurement for Hydraulic Pipe · IEEE Transactions on Instrumentation and Measurement · 2021 · 591 citations
• Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights · Structural Health Monitoring · 2021 · 560 citations
• Nudged Elastic Band Method for Molecular Reactions Using Energy-Weighted Springs Combined with Eigenvector Following · Journal of Chemical Theory and Computation · 2021 · 486 citations
• Machine learning paradigm for structural health monitoring · Structural Health Monitoring · 2020 · 365 citations
• Digital twin, physics-based model, and machine learning applied to damage detection in structures · Mechanical Systems and Signal Processing · 2021 · 354 citations

Most recent work

• Investigation on nonstationary wind effects and intelligent multi-level warning method for wind-induced vibration of bridges · Structures · 2026
• Target-free measurement of cable forces based on video motion magnification and high-order mode shapes · Mechanical Systems and Signal Processing · 2026
• A comprehensive review of indirect bridge health monitoring · Mechanical Systems and Signal Processing · 2026
• Structural health monitoring of offshore wind turbine towers under sparse sensor scenarios based on SEREP-iFEM · Marine Structures · 2026
• Real-time Vehicle-Induced Response Identification via crowdsourced labeling for high-frequency unlabeled sensor data · Engineering Applications of Artificial Intelligence · 2026
• Adaptive forecasting of stochastic crack growth using empirical mode decomposition: Gaussian process regression for structural health monitoring · Structure and Infrastructure Engineering · 2026
• PhysScaleFormer: A multiscale physics-enhanced deep learning framework for real-time dynamic response prediction in vibratory truss structures · Engineering Applications of Artificial Intelligence · 2026
• Acoustic signals-based probabilistic fault diagnosis for expansion joints of small and medium bridges using Bayesian ensemble learning · Engineering Structures · 2026
• Intelligent Structural Health Monitoring of Jack-Up Platform Legs Using High-Density Sensor Networks, Real-Time Digital Twins, and Machine Learning-Based Damage Detection · Future Cities and Environment · 2026
• Transformer-based contrastive denoising autoencoder for unsupervised detection of wind-induced vibration changes in cable-supported bridges · Computer-Aided Civil and Infrastructure Engineering · 2026

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