Long-gauge Sensors Research Articles

Deflection estimation of reinforced concrete beams using long-gauge optic sensors

Deflection is a crucial indicator in structural health monitoring, directly impacting the service life, safety, and economic viability of structures. However, current indirect methods for measuring deflection, such as multi-element FBG sensors or accelerometers, often have limitations. While they may be suitable for flexure-dominated reinforced concrete (RC) specimens in the elastic stage, they neglect the significant influence of nonlinearity and shear deformation. This paper introduces a new approach for estimating the deflection of reinforced concrete (RC) beams using distributed long-gauge optic sensors. The method tackles the limitations of current methods by incorporating the crucial factors of shear deformation, neutral axis position variation and shear stiffness degradation. Experimental studies are first conducted to validate the accuracy and stability of long-gauge optic sensors in small-scale RC members. Algorithms are then utilized the measurement data to estimate the deflection. The results demonstrate the excellent performance of long-gauge optic sensors in measuring shear deformation and vertical deflection of RC beams, as evidenced by comparisons with LVDT measurements. Additionally, a method for decoupling flexural and shear deformation is proposed. This method offers a preliminary assessment of the reinforced concrete (RC) beam type by quantifying the relative significance of shear deformation.

Detection of bridge damage through analysis of dynamic response to vehicular loads utilizing long-gauge sensors

PurposeThis paper presents a novel method for identifying damage in reinforced concrete (RC) bridges, utilizing macro-strain data from distributed long-gauge sensors installed on the concrete surface.Design/methodology/approachThe method relies on the principle that heavy vehicles induce larger dynamic vibrations, leading to increased strain and crack formation compared to lighter vehicles. By comparing the absolute macro-strain ratio (AMSR) of a reference sensor with a network of distributed sensors, damage locations can be effectively pinpointed from a single data collection session. Finite-element modeling was employed to validate the method's efficacy, demonstrating that the AMSR ratio increases significantly in the presence of cracks. Experimental validation was conducted on a real-world bridge in Japan, confirming the method's reliability under normal traffic conditions.FindingsThis approach offers a practical and efficient means of detecting bridge damage, potentially enhancing the safety and longevity of infrastructure systems.Originality/valueOriginal research paper.

Element-wise parallel deep learning for structural distributed damage diagnosis by leveraging physical properties of long-gauge static strain transmissibility under moving loads

The Transmissibility Function (TF) has gained considerable interest in structural damage detection because of its relatively high sensitivity to damage and robustness to excitation. This study proposed a distributed damage diagnosis method for beam-like structures based on a long-gauge static strain TF defined as the ratio of the Fourier transform of static strain response under moving loads from a target long-gauge sensor to that from the reference sensor. It has been discovered that each long-gauge static strain TF is independent of moving loads, making it an ideal damage indicator. It exhibits direct proportionality to the ratio of bending stiffness between the two measured zones covered by the target and reference long-gauge strain sensors while being unaffected by the stiffness of any other zones not covered by these two sensors. Moreover, the TF at zero frequency was proved to be equivalent to the ratio of static strain time history areas, relying solely on the stiffness of the covered zones. Leveraged by the physical properties of long-gauge static strain TF, an element-wise parallel deep neural network architecture was developed to decompose damage diagnosis into independent sub-tasks on the element level, utilizing a variational autoencoder (VAE) in the Bayesian inference framework for extracting features from the long-gauge strain TF and a regressor for mapping the features to elemental stiffness reduction. The divide-and-conquer strategy and element-wise parallel learning architecture allow for a significant reduction in the number of labeled training samples generated based on the updated numerical baseline model as it only requires simulated scenarios involving a single damage element. The efficiency and robustness of the proposed method were demonstrated through a numerical simply supported beam and a laboratory experiment on a two-span bridge.

Full-field static and dynamic strain measurement by an inverse conjugate beam method with two-type sensor placement

This paper presents a novel inverse conjugate beam method (ICBM) to full-field static and dynamic strain measurement using long-gauge fiber Bragg grating (FBG) and vision sensors. By applying reverse analysis of conjugate beam theory, the ICBM establishes a displacement–strain transformation model that effectively explains the correlation between displacement, distributed strain and desired strain. The static and dynamic strain can be reconstructed directly by combining the monitored displacement and strain responses at the displacement monitoring locations. The vision sensor is employed to complement the installed long-gauge strain sensor for monitoring the displacement of the location without a long-gauge sensor. This method helps overcome the difficulty of monitoring the full-bridge strain due to insufficient sensors or inaccessible monitoring positions. At the same time, according to this method, it is necessary to use the displacement from the visual sensor to determine the residual stiffness of each unit as prior information for the ICBM. Both numerical studies and laboratory tests are carried out on a simply supported beam for conceptual verification. The results demonstrate that the proposed ICBM successfully achieves static and dynamic strain response reconstruction at displacement monitoring locations.

Horizontal Deformation Monitoring of Concrete Pile with FRP-Packaged Distributed Optical-Fibre Sensors

Horizontal deformation is a key parameter in the structural assessment of concrete piles, especially in landslide cases. However, the existing deformation-monitoring methods cannot satisfy the demands of long-term monitoring. Therefore, a new method based on distributed optical-fibre sensing technology is proposed for the long-term monitoring of the horizontal deformation of concrete piles. First, a distributed long-gauge optical-fibre sensor is embedded into a fibre-reinforced polymer (FRP) for the excellent distributed strain measurement of the concrete piles in damage cases, such as concrete cracking and reinforcement yielding. Second, based on the typical Winkler beam model, a calculation theory can be constructed for the horizontal deformation of the concrete piles with the input of the strain measurement. Lastly, the proposed method is verified via finite element simulation and static experiments in a laboratory, and the results show good accuracy. Before the case of reinforcement yielding, the largest measurement error of deformation is about 1 mm. It can be up to several millimetres after reinforcement yielding due to the large gap between the calculation model and the actual structure, while the relative measurement error is only about 10%. Due to the distributed strain measurement, the inside horizontal deformation distribution of the concrete piles can be monitored online with the proposed method to implement a detailed assessment of the pile health. Additionally, considering the excellent long-term performance of FRPs and optical-fibre sensors, the proposed method can be applied for the long-term deformation monitoring of concrete piles.

Fatigue Resistance of a BFRP-Encapsulated Long-Gauge FBG Strain Sensor under Cyclic Train Loads

To verify the performance of a basalt fiber reinforced polymer (BFRP) fiber-encapsulated long-gauge strain sensor in railway bridge health monitoring, this paper studies the fatigue resistance and durability of the BFRP fiber-encapsulated FBG sensor under train loads. First, the influences of the length of the anchorage section and the length ratio of the sensing section on the accuracy of the sensor were studied. Then, the BFRP sensor was applied to a sleeper for 2 million cycles of tension fatigue testing. The strain-time history of the whole fatigue test was monitored and compared. After the test, a calibration test was carried out to verify the accuracy and repeatability of the sensor. Finally, the slip and fatigue cracking of the fiber in the anchorage section of the sensor were observed by electron microscopy. The results show that the gap between the anchoring section and the bare optical fiber was filled with epoxy resin, and there was no slip behavior. No fatigue cracking occurred in the fiber, and the strain coefficient and linearity of the sensor showed no obvious changes after 2 million cycles of loading. The long-gauge strain sensor encapsulated by BFRP fibers exhibited good fatigue resistance and can meet long-term monitoring requirements under train loads.

Macro-strain based deflection and neutral axis position monitoring of reinforced concrete beams during corrosion

This article proposes a new technique of monitoring neutral axis positions and deflection of Reinforced Concrete (RC) beam during corrosion of steel reinforcement using macro-strain measurements of distributed long-gauge sensors. A different group of distributed long-gauge Packaged Carbon Fiber Line (PCFL) sensors with self-compensation and effective packaging system is installed on the compression and tension fibers of the concrete surface and steel reinforcements of RC beam to verify the proposed method experimentally. An accelerated corrosion method utilizing a salt solution and the constant current was used to achieve the required corrosion levels. The estimated deflection measured by the developed method is compared with the results using Linear Variable Displacement Transducer (LVDTs). It has been demonstrated that long-gauge PCFL sensors could provide the same accuracy. The distributed measured strains were utilized to evaluate the deterioration of the structure’s health with the advance of corrosion. Based on corrosion monitoring experimental results, it can be confirmed that using distributed PCFL sensors mounted on steel reinforcements or concrete surface, the locations and progress of the damage with corrosion time can be detected effectively. The maximum error in the estimated deflection from PCFL sensors mounted on the concrete surface compared to the LVDTs before the onset and after 24 h of accelerated corrosion was 0.5% and 2.5%, respectively.

Experimental Study on Temperature Sensitivity Coefficient of Long-Gauge Strain Sensor Encapsulated with Fiber

Experimental Study on Temperature Sensitivity Coefficient of Long-Gauge Strain Sensor Encapsulated with Fiber

Study on Graphene-modified FRP Bars Used in the Process of Construction Health Management

The distributed long-gauge optical sensor on fiber reinforced polymer (FRP) bar cannot be manufactured through integrated production in current situation, which is hard for construction management. On the other hand, the point-sensing technology of the self-sensing bar will cause deviations in structural health monitoring (SHM). To solve these issues, applying the graphene/epoxy on FRP members is a feasible method for the piezoresistive characteristics of graphene. In this paper, basalt FRP (BFRP) bars with graphene/epoxy film were tested under repeated and cyclic loads and the resistance was measured at the same time until they were broken down. The results suggested that the test pieces can maintain stable sensing performance under repeated and cyclic loads. These facts indicated that the graphene-modified BFRP bars can well reflect the stress condition of the structural member within a safe range and can maintain stable self-sensing performance in the construction health management.

Study on Self-Sensing Performance of Graphene-Modified FRP Bars

At present, the distributed long-gauge optical sensor on fiber reinforced polymer(FRP) bar cannot be manufactured through integrated production. On the other hand, the point-sensing technology of the self-sensing bar will cause deviations in structural health monitoring (SHM). To solve these issues, applying the graphene/epoxy on FRP members is a feasible method for the piezoresistive characteristics of graphene. In this paper, basalt FRP (BFRP) bars with graphene/epoxy film were tested under static tensile load and the resistance was measured at the same time until they were broken down. The results suggested that the changing rate of resistance was linearly correlated to the strain. This fact indicated that the graphene-modified BFRP bar can well reflect the stress condition of the structural member within a safe range.

Comparative Study of Damage Detection Methods Based on Long-Gauge FBG for Highway Bridges.

Damage detection of highway bridges is a significant part of structural heath monitoring. Conventional accelerometers or strain gauges utilized for damage detection have many shortcomings, especially their monitoring gauge length being too short, which would result in poor damage detection results. Under this circumstance, long-gauge FBG sensors as a novel optical sensor were developed to measure the macro-strain response of the structure. Based on this sensor, many derived damage detection methods were proposed. These methods exhibit various characteristics and have not been systematically compared. As a result, it is difficult to evaluate the state of the art and also leads to confusion for users to select. Therefore, a strict comparative study on three representative methods using long-gauge FBG was carried out. First, these methods’ theoretical backgrounds and formats were reformulated and unified for better comparison. Then, based on validated vehicle–bridge coupling simulation, these methods’ performances were tested through a series of parametric studies including various damage scenarios, vehicle types, speeds, road roughness and noise levels. The precision and reliability of three methods have been thoroughly studied and compared.

Effectiveness of textile reinforced mortar (TRM) materials in preventing seismic-induced damage in a U-shaped masonry structure submitted to pseudo-dynamic excitations

This paper presents the experimental results obtained from tests on a 2/3 scale U-shaped masonry building constructed in one of the ICITECH laboratories at the Universitat Politècnica de València (Spain). The prototype measured 3.31 × 4.19 m2 by 2.15 m high and had a wall thickness of 230 mm. The masonry was composed of 230 × 110 × 50 mm3 solid clay bricks with approximately 10 mm-thick mortar joints arranged in English bond. The tests were aimed at evaluating the effectiveness of cement-based reinforcing materials (Textile Reinforced Mortar) applied to weak masonry substrates severely damaged by horizontal loads such as those induced by a seismic event. The tests were carried out in three phases: (i) testing of the as-built structure, (ii) application of one external layer of TRM to restore the masonry’s original load-bearing capacity and then (iii) testing the TRM-strengthened structure. Dynamic behaviour was monitored by both traditional and fibre optic sensors (FO), including 28 Linear Variable Displacement Transducers (LVDTs) and 3 long-gauge optical sensors. Strengthening effectiveness was evaluated by several parameters: hysteretic curves, strength degradation, computed cumulative energy dissipation and cracking mechanisms. TRM reinforcement was shown to significantly extend the load-bearing and displacement capacity of the masonry prototype, reducing seismic-induced damage applied by pseudo-dynamic excitation, although it had a limited effect on cumulative energy dissipation.

Structural damage detection with distributed long-gauge FBG sensors under multi-point excitations

Distributed strain sensing techniques using long-gauge fiber Bragg grating sensors have been widely applied in health monitoring of civil engineering structures. Developing an effective damage identification method based on the acquired macro-strain is a crucial issue for real applications. In this paper, based on the previous studies on modal macro-strain vector (MMSV) for damage identification under single-point excitation, the damage detection approach under multi-point excitations is further studied. An effective damage index is further proposed as an indicator of the structural damage and the frequency domain decomposition (FDD) technique is introduced to accurately extract the MMSV. The sensitivity and effectiveness of the proposed method for damage detection of a cantilever beam are verified in detail with both numerical simulations and experiments. Results show that both the single and multi damages with different damage extents can be effectively detected under either single point excitations or the wind load excitations. It shows that the proposed approach can do the work well and could be applied for the structural health monitoring of real structures.

Dynamic and quasi-static signal separation method for bridges under moving loads based on long-gauge FBG strain monitoring

Structural health monitoring is an important means of obtaining the state information of bridges, and the extracted quasi-static strain signal can reflect the stress state of bridges directly. However, the strain signals acquired during the operation stage of bridges are dynamic, and the strain gauges used in the health monitoring system are short (no more than 10 cm), which means they are easily affected by small damage at the installation parts of bridges and thereby the monitoring signal abnormalities occur. A type of externally affixed long-gauge fiber strain gauge is used to monitor the health of bridges, and the dynamic and quasi-static signal separation method for long-gauge strain sensors is studied under different vehicle loads; at the same time, the dynamic monitoring performance of the long-gauge sensor is investigated in this paper. The quasi-static strain signal extracted from the dynamic macro-strain signal can be used to directly monitor the stress status of the bridge. The results show that the method proposed in this paper is feasible for extracting the quasi-static macro-strain from a dynamic long-gauge strain signal.

Research on Uplift Bearing Performance of Assembled Steel Pipe Pile used in Transmission Lines in Mountainous Terrain

Assembled steel pipe pile, which is a novel pile foundation, is developed in the paper. The ultimate uplift bearing capacity of the pile is proposed, and simulation by Plaxis3D and the corresponding experiment are performed to verify the theory. In the simulation, ultimate uplift bearing capacity of the assembled steel pipe pile and ultimate lateral frictional resistance of the interface of pile-soil increases with the increasing of the strength and stiffness of the interface of pile-soil, and with the increasing of length-diameter ratio, ultimate uplift bearing capacity of the assembled steel pipe pile increases while the ultimate lateral frictional resistance decreases gradually. The ultimate lateral friction is influenced by both of the strength of the soil around the pile and the interface of pile-soil, and the ultimate uplift bearing capacity obtained by simulation and theoretical calculation are close. Long-gauge FBG sensors are used in the experiment for measuring the longitudinal strain of the pile, and the error of ultimate uplift bearing capacity between the results of experiment and theory is less than 10%.

Prestressing force monitoring method for a box girder through distributed long-gauge FBG sensors

Monitoring prestressing forces is essential for prestressed concrete box girder bridges. However, the current monitoring methods used for prestressing force were not applicable for a box girder neither because of the sensor’s setup being constrained or shear lag effect not being properly considered. Through combining with the previous analysis model of shear lag effect in the box girder, this paper proposed an indirect monitoring method for on-site determination of prestressing force in a concrete box girder utilizing the distributed long-gauge fiber Bragg grating sensor. The performance of this method was initially verified using numerical simulation for three different distribution forms of prestressing tendons. Then, an experiment involving two concrete box girders was conducted to study the feasibility of this method under different prestressing levels preliminarily. The results of both numerical simulation and lab experiment validated this method’s practicability in a box girder.

Normalized Curvature Ratio for Damage Detection in Beam-Like Structures

Fiber optic sensors (FOS) offer numerous advantages for structural health monitoring. In addition to being durable, lightweight, and capable of multiplexing, they offer the ability to monitor strain in both static and dynamic mode. FOS also allow for instrumentation of large areas of a structure with long-gauge sensors which helps enable global monitoring of the structure. Drawing upon these benefits, the Normalized Curvature Ratio (NCR), a curvature based damage detection method, has been developed. This method utilizes a series of long-gauge fiber Bragg grating (FBG) strain sensors for damage detection of a structure through dynamic strain measurements and curvature analysis. The main assumption is that the ratios between cross-sectional curvature amplitudes under free vibration remain unchanged given the state of the structure is unchanged. The theoretical development of this method is presented along with an analytical study of a simply supported beam with two damage cases: a loss of flexural stiffness in the span and a change in rotational stiffness of the support. Validation of the method is then performed through two implementations. First, through a small-scale laboratory test with a simply supported aluminum beam subjected to a change in the rotational stiffness of the support. Second, the method is applied to an existing in-service highway overpass with over 5 years of data collection of dynamic strain events. The advantages and limitations of the method are identified and discussed. This research shows encouraging results and the potential for the NCR to be used as a simplistic metric for damage detection.

Study on Finite Element Model Updating in Highway Bridge Static Loading Test Using Spatially-Distributed Optical Fiber Sensors.

A finite model updating method that combines dynamic-static long-gauge strain responses is proposed for highway bridge static loading tests. For this method, the objective function consisting of static long-gauge stains and the first order modal macro-strain parameter (frequency) is established, wherein the local bending stiffness, density and boundary conditions of the structures are selected as the design variables. The relationship between the macro-strain and local element stiffness was studied first. It is revealed that the macro-strain is inversely proportional to the local stiffness covered by the long-gauge strain sensor. This corresponding relation is important for the modification of the local stiffness based on the macro-strain. The local and global parameters can be simultaneously updated. Then, a series of numerical simulation and experiments were conducted to verify the effectiveness of the proposed method. The results show that the static deformation, macro-strain and macro-strain modal can be predicted well by using the proposed updating model.

Vibration and Deformation Monitoring of a Long-Span Rigid-Frame Bridge with Distributed Long-Gauge Sensors

AbstractAmbient vibration tests and analyses of a long-span rigid-frame bridge were conducted using distributed long-gauge fiber-optic sensors. The concept of a long-gauge fiber-optic sensor and it...

Optimal layout of long-gauge sensors for deformation distribution identification

Structural deflection can be identified from measured strains from long gague sensors, but the sensor layout scheme greatly influences on the accuracy of identified resutls. To determine the optimal sensor layout scheme for accurate deflection identification of the tied arch bridge, the method of optimal layout of long-gauge fiber optic sensors is studied, in which the characteristic curve is first developed by using the bending macro-strain curve under multiple target load conditions, then optimal sensor layout scheme with different number of sensors are determined. A tied arch bridge is studied as an example to verify the effectiveness and robustness of the proposed method for static and dynamic deflection identification.