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Non-contact and full-field strain mapping captures strain across an entire surface, providing a complete two-dimensional (2D) strain distribution without attachment to sensors. It is an essential technique with wide-ranging applications across various industries, significantly contributing to experimental mechanics and structural health monitoring. Although there have been reviews that focus on specific methods, such as interferometric techniques or carbon nanotube-based strain sensors, a comprehensive comparison that evaluates these diverse methods together is lacking. This paper addresses this gap by focusing on strain mapping techniques specifically used in experimental mechanics and structural health monitoring. The fundamental principles of each method are illustrated with specific applications. Their performance characteristics are compared and analyzed to highlight strengths and limitations. The review concludes by discussing future challenges in strain mapping, providing insights into potential advancements and developments in this critical field.

In this paper, a method for detection of crack locations and the width of basin insulators is proposed. Based on the optical frequency domain reflectometry (OFDR) system, the system utilizes an FBG with high feedback for strain as well as temperature, which is affixed to the surface of the tub insulator, and a common single-mode optical fiber, which is used for transmitting data and connected to the optical backscattering reflectometry interrogator. The interrogator measures the backscattered light from the FBG, which varies with temperature or strain. The method has been used to measure the location and width of several different cracks and can locate the crack position with a spatial resolution of 1 mm and measure the crack width with a resolution of 0.77 mm. The method has been used to measure the position and width of insulators. This method provides a simple and fast approach to crack detection in insulators.

Digital Image Correlation (DIC) often encounters challenges with variability and consistency in traditional speckle pattern application techniques, such as spray-painting, affecting measurement accuracy and reliability. This study evaluates a film-free water decal method as an alternative for applying speckle patterns in DIC. SS275 structural steel specimens were prepared with speckle patterns using both the film-free water decal method and traditional spray-painting. The quality of the speckle patterns was assessed, and their effectiveness for DIC was evaluated through tensile testing and a comparison with strain gauge measurements. The film-free water decal method provided enhanced control over speckle pattern application, resulting in high-quality, consistent patterns. Strain measurements obtained using this method closely matched those from traditional methods, confirming its reliability. The film-free water decal method offers a practical and reliable alternative to spray-painting, improving the consistency and accuracy of DIC experiments, with potential applications in various engineering and scientific fields.

The application of distributed fiber optic strain and temperature measurement can be utilized to address a multitude of measurement tasks across a diverse range of fields, particularly in the context of structural health monitoring in the domains of building construction, civil engineering, and special foundation engineering. However, a comprehensive understanding of the influences on the measurement method and the sensors is essential to prevent misinterpretations or measurement deviations. In this context, this study investigated the effects of moisture exposure, including various salt solutions and a high pH value, on a distributed strain measurement using Rayleigh backscattering. Three fiber optic sensors with different coating materials and one uncoated fiber were exposed to five different solutions for 24 h. The study revealed significant discrepancies (∼38%) in deformation between the three coating types depending on the surrounding solution. Furthermore, in contrast to the prevailing literature, which predominantly describes swelling effects, a negative deformation (∼−47 με) was observed in a magnesium chloride solution. The findings of this study indicate that corresponding effects can impact the precision of measurement, potentially leading to misinterpretations. Conversely, these effects could be used to conduct large-scale monitoring of chemical components using distributed fiber optic sensing.

The maximum thickness for ferritic steel specimens’ residual stress measurements using neutron diffraction is known to be about 80 mm. This paper proposes a new neutron diffraction configuration of residual stress measurements for cases that are over 80 mm thick. The configuration utilizes a neutron beam with a wavelength of 1.55 Å diffracted from the (220) plane with a diffraction angle (2θ) of 99.4°. The reason for the deep penetration capability is attributed to the chosen wavelength having enough intensities due to the low cross-section near the Bragg edge and the reduced beam path length (~16 mm) reflected by the large diffraction angle. Neutron diffraction experiments with this configuration can decrease strain errors up to ±150 με, corresponding to a stress of about ±30 MPa.

Strain measurements are vital in engineering trials, testing, and scientific research. In the process of signal acquisition, baseline drift has a significant impact on the accuracy and validity of data. Traditional solutions, such as discrete wavelet transform and empirical mode decomposition, cannot be used in real-time systems. To solve this problem, this paper proposes a Transformer-based model to eliminate the drift in the signal. A self-attentive mechanism is utilized in the encoder of the model to learn the interrelationships between the components of the input signal, and captures the key features. Then, the decoder generates a corrected signal. Meanwhile, a high-precision strain acquisition system is constructed. The experiments tested the model’s ability to remove drift from simulated voltage signals with and without Gaussian noise. The results demonstrated that the transformer model excels at eliminating signal baseline drift. Additionally, the performance of the model was investigated under different temperature conditions and with different levels of force applied by the electronic universal testing machine to produce strain. The experimental results indicate that the Transformer model can largely eliminate drift in dynamic signals l and has great potential for practical applications.

With the recent advances in autonomous vehicles, there is an increasing need for sensors that can help monitor tire–road conditions and the forces that are applied to the tire. The footprint area of a tire that makes direct contact with the road surface, known as the contact patch, is a key parameter for determining a vehicle’s effectiveness in accelerating, braking, and steering at various velocities. Road unevenness from features such as potholes and cracks results in large fluctuations in the contact patch surface area. Such conditions can eventually require the driver to perform driving maneuvers unorthodox to normal traffic patterns, such as excessive pedal depressions or large steering inputs, which can escalate to hazards such as the loss of control or impact. The integration of sensors into the inner liner of a tire has proven to be a promising method for extracting real-time tire-to-road contact patch interface data. In this research, a tire model is developed using Abaqus/CAE and analyzed using Abaqus/Explicit to study the nonlinear behavior of a rolling tire. Strain variations are investigated at the contact patch in three major longitudinal slip driving scenarios, including acceleration, braking, and free-rolling. Multiple vertical loading conditions on the tire are applied and studied. An intelligent tire prototype called KU-iTire is developed and tested to validate the strain results obtained from the simulations. Similar operating and loading conditions are applied to the physical prototype and the simulation model such that valid comparisons can be made. The experimental investigation focuses on the effectiveness of providing usable and reliable tire-to-road contact patch strain variation data under several longitudinal slip operating conditions. In this research, a correlation between FEA and experimental testing was observed between strain shape for free-rolling, acceleration, and braking conditions. A relationship between peak longitudinal strain and vertical load in free-rolling driving conditions was also observed and a correlation was observed between FEA and physical testing.

The facial expressions of humanoid robots play a crucial role in human–computer information interactions. However, there is a lack of quantitative evaluation methods for the anthropomorphism of robot facial expressions. In this study, we designed and manufactured a humanoid robot head that was capable of successfully realizing six basic facial expressions. The driving force behind the mechanism was efficiently transmitted to the silicone skin through a rigid linkage drive and snap button connection, which improves both the driving efficiency and the lifespan of the silicone skin. We used human facial expressions as a basis for simulating and acquiring the movement parameters. Subsequently, we designed a control system for the humanoid robot head in order to achieve these facial expressions. Moreover, we used a flexible vertical graphene sensor to measure strain on both the human face and the silicone skin of the humanoid robot head. We then proposed a method to evaluate the anthropomorphic degree of the robot’s facial expressions by using the difference rate of strain. The feasibility of this method was confirmed through experiments in facial expression recognition. The evaluation results indicated a high degree of anthropomorphism for the six basic facial expressions which were achieved by the humanoid robot head. Moreover, this study also investigates factors affecting the reproduction of expressions. Finally, the impulse was calculated based on the strain curves of the energy consumption of the humanoid robot head to complete different facial expressions. This offers a reference for fellow researchers when designing humanoid robot heads, based on energy consumption ratios. To conclude, this paper offers data references for optimizing the mechanisms and selecting the drive components of the humanoid robot head. This was realized by considering the anthropomorphic degree and energy consumption of each part. Additionally, a new method for evaluating robot facial expressions is proposed.

Distributed optical fibre sensing (DOFS)-based strain measurement systems are now routinely deployed across infrastructure health monitoring applications. However, there are still practical performance and measurement issues associated with the fibre’s attachment method, particularly with thermoplastic pipeline materials (e.g., high-density polyethylene, HDPE) and adhesive affixment methods. In this paper, we introduce a new optical fibre installation method that utilises a hot-weld encapsulation approach that fully embeds the fibre onto the pipeline’s plastic surface. We describe the development, application and benefits of the new embedment approach (as compared to adhesive methods) and illustrate its practical performance via a full-scale, real-world, dynamic loading trial undertaken on a 1.8 m diameter, 6.4 m long stormwater pipeline structure constructed from composite spiral-wound, steel-reinforced, HDPE pipe. The optical frequency domain reflectometry (OFDR)-based strain results show how the new method improves strain transference and dynamic measurement performance and how the data can be easily interpreted, in a practical context, without the need for complex strain transfer functions. Through the different performance tests, based on UK rail-road network transport loading conditions, we also show how centimetre- to metre-scale strain variations can be clearly resolved at the frequencies and levels consistent with transport- and construction-based, buried infrastructure loading scenarios.

To overcome the shortcomings of plowing and rotary tillage, a human-like weeding shoveling machine was designed. The machine’s various moving rods were analyzed using Matlab R2019b(9.7.0.1190202) software to determine the appropriate entry and cutting conditions, as well as non-cutting conditions. It was concluded that a θ2 of 90° was optimal for cutting the soil and that the shoveling depth was suitable for greenhouse weeding. The Adams and DEM coupled discrete element simulation system was developed for this machine and was used to analyze the rotating shaft torque and shovel bending moment. A strain measurement system based on strain gauges was designed to measure the rotating shaft torque and shovel bar bending moment. A bending moment and torque measurement system was designed to perform field measurement tests for comparison with simulation results. The simulation system’s rotating shaft had an average torque error of 6.26%, while the shovel rod’s bending moment had an average error of 5.43%. The simulation accuracy was within the acceptable error range. Table U8 (81 × 44) of the Uniform Design of the Mixing Factor Level for the Homogeneous Virtual Simulation Test includes eight levels of forward machine speed ranging from 0.1 to 0.45 m/s and four levels of output shaft speed ranging from 90 to 165 r/min. Crank lengths were set at four levels ranging from 155 to 185 mm, while shovel lengths were set at four levels ranging from 185 to 230 mm. Four types of shovel shapes were proposed, including pointed curved shovels, pointed straight shovels, straight-edged curved shovels, and straight-edged straight shovels. A mathematical model was created via a regression analysis of the results of coupled simulation tests to establish the relationship between shaft torque and shovel rod bending moment, tool advance speed, shaft speed, crank length, tool length, and tool shape. The model was used to determine the optimum working parameters.

We propose an air gap fiber Bragg grating (g-FBG) sensor that can measure strain and temperature simultaneously. The sensor is made by aligning two fiber Bragg gratings (FBGs), and an air gap exists between these two sub-gratings. This sensor’s architecture allows it to form a spectrum with phase-shifted fiber Bragg grating (PSFBG) spectroscopy and Fabry–Perot interference (FPI) spectroscopy. Since the sensitivity of PSFBG and FPI spectra is different for strain and temperature, it is possible to measure both strain and temperature by measuring one of the reflected dips of PSFBG and the interference dip of FPI. The experimental results show that the strain sensitivity is about 11.95 pm/με via the dip wavelength detection of FPI, and the temperature sensitivity is about 9.64 pm/°C via the dip wavelength detection of PSFBG. The g-FBG sensor demonstrates a resolution of approximately ±3.7 με within the strain range of 0 to 1000 με and about ±0.6 °C within the temperature range of 25 °C to 120 °C. The proposed g-FBG sensor, characterized by its simple structure, compact size, and cost-effectiveness, exhibits significant potential in the field of multi-parameter measurements.

MgB2 represents a hexagonal superconductive material renowned for its straightforward composition, which has facilitated the development of cost-effective practical wires. Its capacity to function at temperatures as low as liquid hydrogen (LH2) has made it a prominent candidate as wire material for the coils of next-generation fusion reactors. Much like other superconducting wires, a prevalent issue arises when these wires are employed in coils, wherein electromagnetic forces induce tensile stress and strain within the wire. This, in turn, diminishes the critical current, which is the maximum current capable of flowing within the generated magnetic field and strain. The techniques and methods for accurately measuring the actual strain on the filaments are of paramount importance. While strain measurements have been conducted with synchrotron radiation and neutrons for other practical wires in the past, no such measurements have been undertaken for MgB2. Presumably, this lack of measurement is attributed to its relatively greater thickness, making it less suitable for synchrotron radiation measurements. Additionally, the high absorption cross-section of the included boron-10 poses challenges in obtaining elastic scattering data for neutron measurements. In response, we fabricated a wire enriched with boron-11, an isotope with a smaller neutron absorption cross-section. We then embarked on the endeavor to measure its strain under tensile loading using pulsed neutrons. Consequently, we succeeded in obtaining changes in the lattice constant under tensile loading through Rietveld analysis. This marks the inaugural instance of strain measurement on an MgB2 filament, signifying a significant milestone in superconductivity research.

This study investigated the use of distributed optical fiber sensing to measure temperature and strain during thermomechanical processes in printed circuit board (PCB) manufacturing. An optical fiber (OF) was bonded to a PCB for simultaneous measurement of temperature and strain. Optical frequency-domain reflectometry was used to interrogate the fiber optic sensor. As the optical fiber is sensitive to both temperature and strain, a demodulation technique is required to separate both effects. Several demodulation techniques were compared to find the best one, highlighting their main limitations. The importance of good estimations of the temperature sensitivity coefficient of the OF and the coefficient of thermal expansion of the PCB was highlighted for accurate results. Furthermore, the temperature sensitivity of the bonded OF should not be neglected for accurate estimations of strains. The two-sensor combination model provided the best results, with a 2.3% error of temperature values and expected strain values. Based on this decoupling model, a methodology for measuring strain and temperature variations in PCB thermomechanical processes using a single and simple OF was developed and tested, and then applied to a trial in an industrial environment using a dynamic oven with similar characteristics to those of a reflow oven. This approach allows the measurement of the temperature profile on the PCB during oven travel and its strain state (warpage).

The knowledge of the operating conditions in rolling bearings in technical applications offers many advantages, for example, to ensure a safe operation and to save resources and costs with the help of condition monitoring and predictive maintenance procedures. In many cases, it is difficult to implement sensors to measure the operating conditions of the rolling bearing, for reasons such as inaccessibility of the mounting position or non-compliance with installation space neutrality, which influences the sensor on the measuring point. Printed sensors using a digital deposition process, which can be used in very narrow design spaces, offer advantages in this respect. So far, these sensors have not been established in rolling bearings, so there is potential for technical application. This paper discusses the fundamental advantages and disadvantages as well as the challenges of the application, and it demonstrates the feasibility under isolated boundary conditions by applying a printed strain gauge sensor to the outer ring of a cylindrical roller bearing NU210 in an experimental setup to measure the strain under load. In this setup, the outer ring is deformed by 2 mm under an increasing radial load using a hydraulic press, and the strain is measured. Both a commercial reference sensor and a FE-simulation are used to validate the measurement. The results show that an implementation using printed sensors as a strain gauge works successfully. The resulting challenges, such as measuring strain gradients and printing on curved surfaces, are finally evaluated, and an outlook for further work is given.

Embedding fiber optic sensors (FOSs) within parts for strain measurement is attracting widespread interest due to its great potential in the field of structural health monitoring (SHM). This work proposes a novel method of embedding FOSs using capillaries within solid structures and investigates fiber positions and orientation uncertainties within capillaries of different sizes and their influences on strain measurement accuracies. To investigate how the fiber positions and orientation variations influence strain measurement accuracy, both analytical and numerical models are utilized to predict strain distributions along embedded fibers at different positions and with different orientations within the specimen. To verify the predictions, a group of specimens made of Aluminum 6082 was prepared, and the specimens in each group had capillaries of 2 mm, 4 mm, and 6 mm diameters, respectively. Fibers were embedded within each specimen using the capillaries. Four-point bending static tests were conducted for each specimen with embedded FOSs, performing in situ strain measurement. Subsequently, the specimens were partitioned into several pieces, and the cross sections were observed to know the real positions of the embedded fiber. Finally, the strain predictions at the real locations of the fiber were compared with the measured strain from the embedded FOSs. The predicted strain distributions as a function of the fiber positions alone and as a function of both the fiber positions and orientations were compared to assess the influence of fiber orientation change. The results from a combination of analytical, numerical, and experimental techniques suggest that the fiber position from the capillary center is the main factor that can influence strain measurement accuracies of embedded FOSs, and potential fiber misalignments within the capillary had a negligible influence. The fiber position-induced measured error increases from 10.5% to 18.5% as the capillary diameter increases from 2 mm to 6 mm. A 2 mm capillary diameter is able to lead to the lowest measurement error in this study and maintains ease of embedding. In addition, it is found that the measured strain always lies within a strain window defined by the strain distribution along capillary boundaries when there are no cracks. This can be further studied for crack detection.

The structural dynamic response of hydraulic turbines needs to be continuously monitored to predict incipient failures and avoid catastrophic breakdowns. Current methods based on traditional off-board vibration sensors mounted on fixed components do not permit inferring loads induced on rotating parts with enough accuracy. Therefore, the present paper assesses the performance of fiber Bragg grating sensors to measure the vibrations induced on a rotating shaft–disc assembly partially submerged in water resembling a hydraulic turbine rotor. An innovative mounting procedure for installing the sensors is developed and tested, which consists of machining a thin groove along a shaft line to embed a fiber-optic array that can pass through the bearings. At the top of the shaft, a rotary joint is used to extract, in real time, the signals to the interrogator. The shaft strain distribution is measured with high spatial resolution at different rotating speeds in air and water. From this, the natural frequencies, damping ratios, and their associated mode shapes are quantified at different operating conditions. Additionally, the change induced in the modes of vibration by the rotation effects is well captured. All in all, these results validate the suitability of this new fiber-optic technology for such applications and its overall better performance in terms of sensitivity and spatial resolution relative to traditional equipment. The next steps will consist of testing this new sensing technology in actual full-scale hydraulic turbines.

A composite optical bench made up of Carbon Fiber Reinforced Polymer (CFRP) skin and aluminum honeycomb has been developed for the Tunable Magnetograph instrument (TuMag) for the SUNRISE III mission within the NASA Long Duration Balloon Program. This optical bench has been designed to meet lightweight and low sensitivity to thermal gradient requirements, resulting in a low Coefficient of Thermal Expansion (CTE). In addition to the flight model, a breadboard model identical to the flight one has been manufactured, including embedded fiber Bragg temperature and strain sensors. The aim of this is to explore if the use of distributed fiber Bragg gratings (FBGs) can provide valuable information for strain and temperature mapping of an optical instrument on board a space mission during its operation as well as its on-ground testing. Furthermore, surface-mounted strain FBG sensors and thermocouples have been installed in the optical bench for intercomparison purposes. This paper presents the results obtained from a thermal vacuum test consisting of three thermal cycles with stabilization steps at 100 °C, 60 °C, 20 °C and −20 °C. Experimental results provide information about how FBG embedded temperature sensors can provide a proper and quick response to the temperature changes of the optical bench and that embedded FBG strain sensors are able to measure micro-deformation induced in a close-to-zero CTE optical bench.

Near-field passive wireless sensors can realize non-contact strain measurement, so these sensors have extensive applications in structural health monitoring. However, these sensors suffer from low stability and short wireless sensing distance. This paper presents a bulk acoustic wave (BAW) passive wireless strain sensor, which consists of two coils and a BAW sensor. The force-sensitive element is a quartz wafer with a high quality factor, which is embedded into the sensor housing, so the sensor can convert the strain of the measured surface into the shift of resonant frequency. A double-mass-spring-damper model is developed to analyze the interaction between the quartz and the sensor housing. A lumped parameter model is established to investigate the influence of the contact force on the sensor signal. Experiments show that a prototype BAW passive wireless sensor has a sensitivity of 4 Hz/με when the wireless sensing distance is 10 cm. The resonant frequency of the sensor is almost independent of the coupling coefficient, which indicates that the sensor can reduce the measurement error caused by misalignment or relative movement between coils. Thanks to the high stability and modest sensing distance, this sensor may be compatible with a UAV-based monitoring platform for the strain monitoring of large buildings.

We proposed an optical frequency domain reflectometry based on a multilayer perceptron. A classification multilayer perceptron was applied to train and grasp the fingerprint features of Rayleigh scattering spectrum in the optical fiber. The training set was constructed by moving the reference spectrum and adding the supplementary spectrum. Strain measurement was employed to verify the feasibility of the method. Compared with the traditional cross-correlation algorithm, the multilayer perceptron achieves a larger measurement range, better measurement accuracy, and is less time-consuming. To our knowledge, this is the first time that machine learning has been introduced into an optical frequency domain reflectometry system. Such thoughts and results would bring new knowledge and optimization to the optical frequency domain reflectometer system.

As wind energy is paving the way for the energy transition from fossil to renewable energy sources, the ongoing trend of increasing the rated power of wind turbines aims to reduce the overall cost of wind energy. The resulting increase in drivetrain loads motivates the need for wind turbine (WT) drivetrain testing in the development phase of critical components such as the WT main gearbox (GB). While several WT system test benches allow for the application of emulated rotor loads in six degrees of freedom (6-DOF), the drivetrain input loads can significantly differ from the GB 6-DOF input loads due to the design of the drivetrain under test. However, currently available load measurement solutions are not capable of sensing GB input loads in 6-DOF. Thus, this work aims to develop a methodology for converging signals from a purposely designed sensor setup and turbine specific design parameters to compute the GB 6-DOF input loads during WT testing. Strain gauges (SG) and accelerometers have been installed on the low-speed shaft (LSS) of a WT drivetrain under test at the 4MW WT system test bench at the Center for Wind Power Drives. Using the data of the aforementioned sensors, a methodology for computing the GB input loads is developed. The methodology is validated through comparison to the applied loads data provided by the aforementioned test bench. The results demonstrate the high promise of the proposed method for estimating the GB input loads during WT drivetrain testing.

Digital image correlation methods allow the determination of the displacement (and thus the strain) field of a target by picture comparisons, without the application of strain gauges or other invasive devices. Homologous sites are mapped from the undeformed to the deformed configuration, and displacements retrieved at a cloud of points in a scattered fashion. Radial basis functions (RBF) offer a rapid and reliable tool to post-process on-the-fly data from image correlation, in order to compute deformations directly without the need for generating a numerical grid over the measurement points. Displacements and associated strains can be computed only where desired, tracking automatically only the most reliable features for each image. In this work, a post-processing strain evaluation method for large displacement problems, based on RBF and the Green–Lagrange tensor, is presented and demonstrated for several test cases. At first, the proposed method is adopted on a set of artificially generated pictures, demonstrating a faster convergence with respect to FEM even when few points are used. Finally, the approach is applied to cases for which experimental results are available in the literature, exhibiting a good agreement.

Fiber-optic sensors are a powerful tool to investigate physical properties like temperature, strain, and pressure. Such properties make these sensors interesting for many applications including biomedical applications. Fiber sensors are also a great platform for distributed sensing by using the principles of optical frequency domain reflectometry. Distributed sensing is becoming more and more used to achieve high-resolution measurements and to map physical properties of biomaterials at small scale, thus obtaining 2D and 3D mapping of a particular area of interest. This work aims at building and investigating a 2D sensing carpet based on a distributed fiber sensing technique, to map local pressure applied to the carpet. The two-dimensional mapping is obtained by embedding a single-mode optical fiber inside a soft silicone carpet. The fiber has been bent and arranged in a specific configuration characterized by several parallel lines. Different fiber fixation methods have been investigated by means of a comparative analysis to perform better characterization and to achieve a more precise response of the carpet. The best pressure sensitivity coefficient (0.373 pm/kPa or considering our setup 1.165 nm/kg) was detected when the fiber was fully embedded inside the silicone carpet. This paper demonstrates the possibility of mapping a 2D distributed pressure over a surface with a resolution of 2 mm by 2 mm. The surface of investigation is 2 cm by 6 cm, containing 310 sensing points. The sensing carpet has been validated selecting several preferential positions, by testing the consistency of the results over different portions of the carpet.

Nonunion is one of the most dreaded complications after operative treatment of mandible fractures or after mandible reconstruction using vascularized and non-vascularized bone grafts. Often diagnosis is made at advanced stage of disease when pain or complications occur. Devices that monitor fracture healing and bone regeneration continuously are therefore urgently needed in the craniomaxillofacial area. One promising approach is the strain measurement of plates. An advanced prototype of an implantable strain measurement device was tested after fixation to a locking mandible reconstruction plate in multiple compression experiments to investigate the potential functionality of strain measurement in the mandibular region. Compression experiments show that strain measurement devices work well under experimental conditions in the mandibular angle and detect plate deformation in a reliable way. For monitoring in the mandibular body, the device used in its current configuration was not suitable. Implant strain measurement of reconstruction plates is a promising methodical approach for permanent monitoring of bone regeneration and fracture healing in the mandible. The method helps to avoid or detect complications at an early point in time after operative treatment.

Machine learning methods were applied to data with an atmospheric corrosion monitoring sensor based on strain measurements to improve the evaluation accuracy of the thickness reduction of a low-carbon steel plate due to atmospheric corrosion. Monitoring data used in this study were taken in a previous study using active–dummy strain gauges for corrosion product experiments. Values measured by the gauges before inducing corrosion via saltwater treatment of the test piece and reference data of the thickness reduction in a reference test piece were used for training data. By using the trained machine learning methods, the errors for the outputs of the machine learning models were smaller than those for the evaluation in monitoring data of our previous study.

Quantitative dynamic strain measurements of the ground would be useful for engineering scale problems such as monitoring for natural hazards, soil-structure interaction studies, and non-invasive site investigation using full waveform inversion (FWI). Distributed acoustic sensing (DAS), a promising technology for these purposes, needs to be better understood in terms of its directional sensitivity, spatial position, and amplitude for application to engineering-scale problems. This study investigates whether the physical measurements made using DAS are consistent with the theoretical transfer function, reception patterns, and experimental measurements of ground strain made by geophones. Results show that DAS and geophone measurements are consistent in both phase and amplitude for broadband (10 s of Hz), high amplitude (10 s of microstrain), and complex wavefields originating from different positions around the array when: (1) the DAS channels and geophone locations are properly aligned, (2) the DAS cable provides good deformation coupling to the internal optical fiber, (3) the cable is coupled to the ground through direct burial and compaction, and (4) laser frequency drift is mitigated in the DAS measurements. The transfer function of DAS arrays is presented considering the gauge length, pulse shape, and cable design. The theoretical relationship between DAS-measured and pointwise strain for vertical and horizontal active sources is introduced using 3D elastic finite-difference simulations. The implications of using DAS strain measurements are discussed including directionality and magnitude differences between the actual and DAS-measured strain fields. Estimating measurement quality based on the wavelength-to-gauge length ratio for field data is demonstrated. A method for spatially aligning the DAS channels with the geophone locations at tolerances less than the spatial resolution of a DAS system is proposed.

Fused filament fabrication (FFF) is a widely used additive manufacturing process that can produce parts from thermoplastics. Its ease of operation and wide variety of materials make it a popular choice for manufacturing. To leverage such benefits, the commonly used thermoplastics (e.g., PLA and ABS) are impregnated with nanoparticles, short or continuous fibers, and other additives. The addition of graphene nanoplatelets to PLA makes for a high-quality filament possessing enhanced mechanical, electrical, and thermal properties. Even with the advancement in materials, the optimisation of the process parameter remains the most complex aspect for FFF. Therefore, this study investigates the influence of two under-researched and overlooked processing parameters (material extrusion rates and line widths) on commercially available graphene-enhanced PLA (GPLA). Nine different material extrusion rates (70% to 150%) and five different line widths (0.2 mm to 1 mm) were used to manufacture GPLA specimens using a low-cost, desktop-based 3D printer, as per British and international standards. The study analyses the influence of these two processing parameters on mass, dimensional accuracy, surface texture, and mechanical properties of GPLA specimens. A non-destructive test has also been conducted and correlated with three-point flexural test to establish its applicability in evaluating flexural properties of GPLA. The results how that small line widths provide more accuracy with longer print times whereas large line widths offer more strength with shorter printing times. Increase in material extrusion rates adversely affect the surface finish and hardness but positively influence the flexural strength of GPLA specimens. The study shows that the manipulation of material extrusion rates and line widths can help designers in understanding the limitations of the default printing settings (100% material extrusion rate and 0.4 mm line width) on most desktop 3D printers and identifying the optimal combination to achieve desired properties using the FFF process.

Distributed fibre optical sensing (DFOS) is increasingly used in civil engineering research. For reinforced concrete structures, almost continuous information concerning the deformations of embedded reinforcing bars can be obtained. This information enables the validation of basic and conventional assumptions in the design and modelling of reinforced concrete, particularly regarding the interaction of concrete and reinforcing bars. However, this relatively new technology conceals some difficulties, which may lead to erroneous interpretations. This paper (i) discusses the selection of sensing fibres for reinforced concrete instrumentation, accounting for strain gradients and local anomalies caused by stress concentrations due to the reinforcing bar ribs; (ii) describes suitable methods for sensor installation, strain acquisition and post-processing of the data, as well as determining and validating structurally relevant entities; and (iii) presents the results obtained by applying DFOS with these methods in a variety of experiments. The analysed experiments comprise a reinforced concrete tie, a pull-out test under cyclic load, and a flexural member in which the following mechanical relevant quantities are assessed: the initial strain state in reinforcing bars, normal and bond shear stresses, deflections as well as forces. These applications confirm the benefit of DFOS to better understand the bond behaviour, but also demonstrate that its application is intricate and the results may lead to erroneous conclusions unless evaluated meticulously.

In this paper, with the final aim of shape sensing for a morphing aircraft wing section, a developed multimodal shape sensing system is analysed. We utilise the method of interrogating a morphing wing section based on the principles of both hybrid interferometry and Fibre Bragg Grating (FBG) spectral sensing described in our previous work. The focus of this work is to assess the measurement performance and analyse the errors in the shape sensing system. This includes an estimation of the bending and torsional deformations of an aluminium mock-up section due to static loading that imitates the behaviour of a morphing wing trailing edge. The analysis involves using a detailed calibration procedure and a multimodal sensing algorithm to measure the deflection and shape. The method described In this paper, uses a standard single core optical fibre and two grating pairs on both the top and bottom surfaces of the morphing section. A study on the fibre placement and recommendations for efficient monitoring is also included. The analysis yielded a maximum deflection sensing error of 0.7 mm for a 347 × 350 mm wing section.

Water impacts provide a challenge for a wide range of applications, from aerospace, to marine, mechanical and civil engineering, due to the complexity conveyed by the coexistence of impulsive loads, large local deformations and high-amplitude vibrations. Thus, the need for reliable structural health monitoring (SHM) systems is emerging in the industrial field of fluid-structure interaction (FSI) applications. In this paper, we leverage the previous work on strain and displacement fields reconstruction to analyse a scale aluminium model subject to water vertical and oblique impacts. Fibre Bragg grating (FBG) sensors were installed on the hull ribs and used both as reconstruction sensors (to reconstruct the structure mechanical behaviour characteristics) and as control sensors, by using their signals to compare the real and reconstructed structural parameters, at the sensors locations. Finally, the effectiveness of different reconstruction layouts was investigated referring to the strain signal reconstruction quality in case of both vertical and oblique impacts. Results show the potential of the described method for the reconstruction of strain signal through a proper choice of the reconstruction sensors positions both in case of vertical and oblique impacts.

The strain in a fast spinning carbon fiber flywheel rotor is of great interest for condition monitoring, as well as for studying long-term aging effects in the carbon fiber matrix. Optoelectronic strain measurement is a contactless measurement principle where a special reflective pattern is applied to the rotor which is scanned by a stationary optical setup. It does not require any active electronic components on the rotor and is suited for operation in a vacuum. In this paper, the influences of the key parts comprising the optoelectronic strain measurement are analyzed. The influence of each part on the measurement result including the uncertainty is modeled. The total uncertainty, as well as each part’s contribution is calculated. This provides a valuable assessment of requirements for component selection, as well as tolerances of mechanical parts and processes to reach a final target measurement uncertainty or to estimate the uncertainty of a given setup. We have shown that the edge quality of the special reflective pattern has the strongest influence, and how to improve it. Considering all influences, it is possible to measure strain with an uncertainty of less than 1% at a rotation speed of 500Hz.

The present study investigates the environmental durability of a distributed optical fiber sensing (DOFS) cable on the market, commonly used for distributed strain measurements in reinforced concrete structures. An extensive experimental program was conducted on different types of specimens (including samples of bare DOFS cable and plain concrete specimens instrumented with this DOFS cable) that were exposed to accelerated and natural ageing (NA) conditions for different periods of up to 18 months. The instrumentation of both concrete specimens consisted of DOFS cables embedded at the center of the specimens and bonded at the concrete surface, as these two configurations are commonly deployed in the field. In these configurations, the alkalinity of the surrounding cement medium and the outdoor conditions are the main factors potentially affecting the characteristics of the DOFS component materials and the integrity of the various interfaces, and hence impacting the strain transfer process between the host structure and the core optical fiber (OF). Therefore, immersion in an alkaline solution at an elevated temperature or freeze/thaw (F/T) and immersion/drying (I/D) cycles were chosen as accelerated ageing conditions, depending on the considered configuration. Mechanical characterizations by tensile and pull-out tests were then carried out on the exposed specimens to assess the evolution of the mechanical properties of individual component materials as well as the evolution of bond properties at various interfaces (internal interfaces of the DOFS cable, and interface between the cable and the host structure) during ageing. Complementary physico-chemical characterizations were also performed to better understand the underlying degradation processes. The experimental results highlight that immersion in the alkaline solution induced a significant and rapid decrease in the bond properties at internal interfaces of the DOFS cable and at the cable/concrete interface (in the case of the embedded cable configuration), which was assigned to chemical degradation at the surface of the cable coating in contact with the solution (hydrolysis and thermal degradation of the EVA copolymer component). Meanwhile, F/T and I/D cycles showed more limited effects on the mechanical properties of the component materials and interfaces in the case of the bonded cable configuration. A comparison with the same specimens exposed to outdoor NA suggested that the chosen accelerated ageing conditions may not be totally representative of actual service conditions, but provided indications for improving the ageing protocols in future research. In the last part, an analysis of the distributed strain profiles collected during pull-out tests on instrumented concrete specimens clearly illustrated the consequences of ageing processes on the strain response of the DOFS cable.

A variety of specialty fibers such as no-core fiber (NCF) have already been studied to reveal their sensing abilities. In this work, we investigate a specialty fiber, square-core fiber, for temperature and strain sensing. A simple single-mode–multimode–single-mode (SMS) fiber sensor was fabricated, consisting of a 30-cm-long square-core fiber. The experimental results indicate that the maximal wavelength-temperature and wavelength-strain sensitivities are −15.3 pm/∘C and −1.5 pm/με, respectively, while the maximal power-temperature and power-strain sensitivities are 0.0896 dBm/∘C and 0.0756 dBm/με. Analysis of the results suggests that the fiber sensor has the potential to be used as a high-sensitivity temperature sensor with a low strain sensitivity.

Nanomodified smart cement-based sensors are an emerging self-sensing technology for the structural health monitoring (SHM) of reinforced concrete (RC) structures. To date, several literature works demonstrated their strain-sensing capabilities, which make them suited for damage detection and localization. Despite the most recent technological improvements, a tailored measurement technique allowing feasible field implementations of smart cement-based sensors to concrete structures is still missing. In this regard, this paper proposes a multichannel measurement technique for retrieving strains from smart cement-based sensors embedded in RC structures using a distributed biphasic input. The experiments performed for its validation include the investigation on an RC beam with seven embedded sensors subjected to different types of static loading and a long-term monitoring application on an RC plate. Results demonstrate that the proposed technique is effective for retrieving time-stable simultaneous strain measurements from smart cement-based sensors, as well as for aiding the identification of the changes in their electrical outputs due to the influence of environmental effects variable over time. Accordingly, the proposed multichannel strain measurement technique represents a promising approach for performing feasible field implementations of smart cement-based sensors to concrete structures.

The facial expressions of humanoid robots play a crucial role in human-computer information interactions. However, there is a lack of quantitative evaluation methods for the anthropomorphism of robot facial expressions. In this study, we designed and manufactured a humanoid robot head that was capable of successfully realizing six basic facial expressions. The driving force behind the mechanism was efficiently transmitted to the silicone skin through a rigid linkage drive and snap button connection, which improves both the driving efficiency and the lifespan of the silicone skin. We used human facial expressions as a basis for simulating and acquiring the movement parameters. Subsequently, we designed a control system for the humanoid robot head in order to achieve these facial expressions. Moreover, we used a flexible vertical graphene sensor to measure strain on both the human face and the silicone skin of the humanoid robot head. We then proposed a method to evaluate the anthropomorphic degree of the robot's facial expressions by using the difference rate of strain. The feasibility of this method was confirmed through experiments in facial expression recognition. The evaluation results indicated a high degree of anthropomorphism for the six basic facial expressions which were achieved by the humanoid robot head. Moreover, this study also investigates factors affecting the reproduction of expressions. Finally, the impulse was calculated based on the strain curves of the energy consumption of the humanoid robot head to complete different facial expressions. This offers a reference for fellow researchers when designing humanoid robot heads, based on energy consumption ratios. To conclude, this paper offers data references for optimizing the mechanisms and selecting the drive components of the humanoid robot head. This was realized by considering the anthropomorphic degree and energy consumption of each part. Additionally, a new method for evaluating robot facial expressions is proposed.

The need for effective and reliable damage detection and localization systems is growing in several engineering fields, in particular in water impact problems characterized by impulsive loading conditions, high amplitude vibrations and large local deformations. In this paper, we further develop the approach presented in previous works to detect damage of water-impacting structures. Specifically, we provide a set of experimental tests on a flexible plastic cylinder impacting the water after a 50 cm free fall. The cylindrical specimen is artificially damaged in a known position. Strain measurements are performed through a set of nine fiber Bragg gratings distributed along the circumference of a cylinder section. We show that strain sensors can be used as reference sensors, for structure displacements reconstruction, and control sensors, for damage detection purposes, and the computation of the difference between measured and expected deformation may allow damage detection. Moreover, we investigate how exchanging control and reference sensors in the same sensor arrangement affect damage detection and localization.

Optical fiber sensors have been potentially expected to apply in the extreme environment for their advantages of measurement in a large temperature range. The packaging measure which makes the strain sensing fiber survive in these harsh conditions will commonly introduce inevitable strain transfer errors. In this paper, the strain transfer characteristics of a multi-layer optical fiber sensing structure working at cryogenic environment with temperature gradients have been investigated theoretically. A generalized three-layer shear lag model incorporating with temperature-dependent properties of layers was developed. The strain transfer relationship between the optical fiber core and the matrix has been derived in form of a second-order ordinary differential equation (ODE) with variable coefficients, where the Young’s modulus and the coefficients of thermal expansion (CTE) are considered as functions of temperature. The strain transfer characteristics of the optical sensing structure were captured by solving the ODE boundary problems for cryogenic temperature loads. Case studies of the cooling process from room temperature to some certain low temperatures and gradient temperature loads for different low-temperature zones were addressed. The results showed that different temperature load configurations cause different strain transfer error features which can be described by the proposed model. The protective layer always plays a main role, and the optimization geometrical parameters should be carefully designed. To verify the theoretical predictions, an experiment study on the thermal strain measurement of an aluminum bar with optical fiber sensors was conducted. LUNA ODiSI 6100 integrator was used to measure the Rayleigh backscattering spectra shift of the optical fiber at a uniform temperature and a gradient temperature under liquid nitrogen temperature zone, and a reasonable agreement with the theory was presented.

Smooth integration of intermittent energy sources, such as solar and wind power, into the electrical grid induces new operating conditions of the hydraulic turbine by increasing the off-design operations, start/stops, and load variations. Therefore, hydraulic turbines are subject to unstable flow conditions and unfavorable load fluctuations. Predicting load fluctuations on the runner using indirect measurements can allow for optimized operations of the turbine units, increase turbine refurbishment time intervals, and avoid structural failures in extreme cases. This paper investigates an experimental methodology to assess and predict the flow condition and load fluctuations on a Kaplan turbine runner at several steady-state operations by performing measurements on the shaft in the rotating and stationary frame of references. This unit is instrumented with several transducers such as miniature pressure transducers, strain gages, and proximity probes. The results show that for any propeller curve of a Kaplan turbine, the guide vane opening corresponding to the minimum pressure and strain fluctuations on the runner blade can be obtained by axial, torsion, and bending measurements on the shaft. Torsion measurements on the shaft could support index-testing in Kaplan turbines particularly for updating the cam-curve during the unit operation. Furthermore, a signature of every phenomenon observed on the runner blade signals, e.g., runner frequency, rotating vortex rope components, and rotor-stator interaction, is found in the data obtained from the shaft.

The aim of operational load monitoring is to make predictions about the remaining usability time of structures, which is extremely useful in aerospace industry where in-service life of aircraft structural components can be maximized, taking into account safety. In order to make such predictions, strain sensors are mounted to the structure, from which data are acquired during operational time. This allows to determine how many load cycles has the structure withstood so far. Continuous monitoring of the strain distribution of the whole structure can be complicated due to vicissitude nature of the loads. Sensors should be mounted in places where stress and strain accumulations occur, and due to experiencing variable loads, the number of required sensors may be high. In this work, different machine learning and artificial intelligence algorithms are implemented to predict the current safety factor of the structure in its most stressed point, based on relatively low number of strain measurements. Adaptive neuro-fuzzy inference systems (ANFIS), support-vector machines (SVM) and Gaussian processes for machine learning (GPML) are trained with simulation data, and their effectiveness is measured using data obtained from experiments. The proposed methods are compared to the earlier work where artificial neural networks (ANN) were proven to be efficiently used for reduction of the number of sensors in operational load monitoring processes. A numerical comparison of accuracy and computational time (taking into account possible real-time applications) between all considered methods is provided.

The article describes four-point bending tests of three reinforced concrete beams with identical cross-sections, spans, and high-ductility steel reinforcement systems. Two beams were strengthened in the compressed section with a thin layer of reactive powder concrete (RPC) bonded with evenly spaced stirrups. Their remaining sections, and the third reference beam, were made of ordinary concrete. Measurements of their deflections, strains and axis curvature; ultrasonic tests; and a photogrammetric analysis of the beams are the main results of the study. For one of the beams with the RPC, the load was increased in one stage. For the two remaining beams, the load was applied in four stages, increasing the maximum load from stage to stage in order to allow the analysis of the damage evolution before reaching the bending resistance. The most important effect observed was the stable behaviour of the strengthened beams in the post-critical state, as opposed to the reference beam, which had about two to three times less energy-absorbing capacity in this range. Moreover, thanks to the use of the RPC layer, the process of concrete cover delamination in the compression zone was significantly reduced, the high ductility of the rebars was fully utilized during the formation of plastic hinges, and the bending capacity was increased by approximately 12%.

The present study investigated the strain response of a distributed optical fiber sensor (DOFS) sealed in a groove at the surface of a concrete structure using a polymer adhesive and aimed to identify optimal conditions for crack monitoring. A finite element model (FEM) was first proposed to describe the strain transfer process between the host structure and the DOFS core, highlighting the influence of the adhesive stiffness. In a second part, mechanical tests were conducted on concrete specimens instrumented with DOFS bonded/sealed using several adhesives exhibiting a broad stiffness range. Distributed strain profiles were then collected with an interrogation unit based on Rayleigh backscattering. These experiments showed that strain measurements provided by DOFS were consistent with those from conventional sensors and confirmed that bonding DOFS to the concrete structure using soft adhesives allowed to mitigate the amplitude of local strain peaks induced by crack openings, which may prevent the sensor from early breakage. Finally, the FEM was generalized to describe the strain response of bonded DOFS in the presence of crack and an analytical expression relating DOFS peak strain to the crack opening was proposed, which is valid in the domain of elastic behavior of materials and interfaces.

Using the relationship between strain and thickness from the materials theory, this paper presents further development of the atmospheric corrosion sensor based on strain measurement (ACSSM). Fiber Bragg grating (FBG) sensors were used to measure strain in this study. The active–dummy method was employed to compensate the effects of environmental temperature drift, with the configuration and position of the active–dummy FBG sensors determined based on simulations conducted using the finite element method (FEM). Hence, the reduction in thickness of low-carbon steel test pieces could be isolated, ensuring accurate characterization of this parameter. Results of practical galvanostatic electrolysis experiments conducted with the FBG sensors in the proposed configuration demonstrated accurate measurement of the reduction in the thickness of a test piece, suggesting that an ACSSM with active–dummy FBG sensors would be appropriate for monitoring of atmospheric corrosion in steel structures.

The objective of this study is to evaluate and improve the accuracy and stability of a strain measurement method that uses the speeded-up robust feature (SURF) method to trace the displacement of feature points in microimages and obtain the strain in objects. The microimages were acquired using a smartphone with a portable microscope, which has a broad prospect of application. An experiment was performed using an unpacked optical fiber as the experimental carrier. The matching effect of the SURF method was analyzed in the microimage, and the M-estimator sample consensus (MSAC) algorithm was used to reject outliers generated by SURF. The results indicated that the accuracy of strain measurement using the proposed method is improved by modifying the feature point tracking method and measurement method. When compared with the fiber Bragg grating (FBG) data, the maximum standard error corresponded to 2.5 με, which satisfies the requirement of structural health monitoring (SHM) in practical engineering.

This article presents the use of a sensor with fiber Bragg grating along with an interrogation system used for monitoring the overhead lines’ wire elongation. The possible interrogation methods based on adjusted filters were considered. In the experimental part, three types of fiber Bragg grating pairs, characterized by a small shift in spectra in pairs and gratings with exact matching, were examined. The study showed that, by choosing the appropriate mechanical parameters of the elongation transformer with the optical parameters of the sensor and dedicated filter, the optomechanical system can be adjusted to the required range of overhead line wire sag observation. The range of sag depends on the distance between the poles, the wire type, and its real length in the span, which effectively determines the sag.

Operational Load Monitoring consists of the real-time reading and recording of the number and level of strains and stresses during load cycles withstood by a structure in its normal operating environment, in order to make more reliable predictions about its remaining lifetime in service. This is particularly important in aeronautical and aerospace industries, where it is very relevant to extend the components useful life without compromising flight safety. Sensors, like strain gauges, should be mounted on points of the structure where highest strains or stresses are expected. However, if the structure in its normal operating environment is subjected to variable exciting forces acting in different points over time, the number of places where data will have be acquired largely increases. The main idea presented in this paper is that instead of mounting a high number of sensors, an artificial neural network can be trained on the base of finite element simulations in order to estimate the state of the structure in its most stressed points based on data acquired just by a few sensors. The model should also be validated using experimental data to confirm proper predictions of the artificial neural network. An example with an omega-stiffened composite structural panel (a typical part used in aerospace applications) is provided. Artificial neural network was trained using a high-accuracy finite element model of the structure to process data from six strain gauges and return information about the state of the panel during different load cases. The trained neural network was tested in an experimental stand and the measurements confirmed the usefulness of presented approach.

This article investigates the possibility of applying weldable optic fiber sensors to the corrugated rebar in reinforced concrete structures to detect cracks and measure the deformation of the steel. Arrays have initially been designed comprised of two weldable optic fiber sensors, and one temperature sensor to compensate its effect in measuring deformations. A series of tests were performed on the structures to evaluate functioning of the sensors, and the results obtained from the deformation measures shown by the sensors have been stored using specific software. Two reinforced concrete beams simply resting on the support have been designed to perform the tests, and they have been monitored in the zones with maximum flexion moment. Different loading steps have been applied to the beams at the center of the span, using a loading cylinder, and the measurement of the load applied has been determined using a loading cell. The analysis of the deformation measurements of the corrugated rebar obtained by the optic fiber sensors has allowed us to determine the moment at which the concrete has cracked due to the effect of the loads applied and the deformation it has suffered by the effect of the different loading steps applied to the beams. This means that this method of measuring deformations in the corrugated rebar by weldable optic fiber sensors provides very precise results. Future lines of research will concentrate on determining an expression that indicates the real cracking moment of the concrete.

The paper presents application of different sensors for the purpose of short and long term measurements, as well as a structural health monitoring (SHM) system to assess the behavior of a novel fiber reinforced plastics (FRP) composite footbridge. The aim is to present a thorough and concise description of these sensors networks and results gathered with their aid during in situ measurement of strains, displacements, and vibrations, as only a few works are available in this field. The bridge geometry, material solutions, and properties are described at first. Then the measurement devices composing the system and subsystems of sensors are elaborated on. Subsequently, the bridge research program is described and the results are shown and discussed. Finally, it is concluded that the use of selected sensors is helpful in assessment of the behavior of the novel structure, and moreover in validation of its numerical models. The collected data confirmed many assumptions made during the bridge design process and allowed us to accept it for exploitation.

A review of recent research on structural monitoring in railway industry is proposed in this paper, with a special focus on stress-based solutions. After a brief analysis of the mechanical behaviour of ballasted railway tracks, an overview of the most common monitoring techniques is presented. A special attention is paid on strain gages and accelerometers for which the accurate mounting position on the track is requisite. These types of solution are then compared to another modern approach based on the use of optical fibres. Besides, an in-depth discussion is made on the evolution of numerical models that investigate the interaction between railway vehicles and tracks. These models are used to validate experimental devices and to predict the best location(s) of the sensors. It is hoped that this review article will stimulate further research activities in this continuously expanding field.

We propose a novel method to improve the spatial resolution of Brillouin optical time-domain reflectometry (BOTDR), referred to as synthetic BOTDR (S-BOTDR), and experimentally verify the resolution improvements. Due to the uncertainty relation between position and frequency, the spatial resolution of a conventional BOTDR system has been limited to about one meter. In S-BOTDR, a synthetic spectrum is obtained by combining four Brillouin spectrums measured with different composite pump lights and different composite low-pass filters. We mathematically show that the resolution limit, in principle, for conventional BOTDR can be surpassed by S-BOTDR and experimentally prove that S-BOTDR attained a 10-cm spatial resolution. To the best of our knowledge, this has never been achieved or reported.

In this paper, the characterization of the main techniques and transducers employed to measure local and global strains induced by uniaxial loading of murine tibiae is presented. Micro strain gauges and digital image correlation (DIC) were tested to measure local strains, while a moving coil motor-based length transducer was employed to measure relative global shortening. Local strain is the crucial parameter to be measured when dealing with bone cell mechanotransduction, so we characterized these techniques in the experimental conditions known to activate cell mechanosensing in vivo. The experimental tests were performed using tibia samples excised from twenty-two C57BL/6 mice. To evaluate measurement repeatability we computed the standard deviation of ten repetitive compressions to the mean value. This value was lower than 3% for micro strain gauges, and in the range of 7%−10% for DIC and the length transducer. The coefficient of variation, i.e., the standard deviation to the mean value, was about 35% for strain gauges and the length transducer, and about 40% for DIC. These results provided a comprehensive characterization of three methodologies for local and global bone strain measurement, suggesting a possible field of application on the basis of their advantages and limitations.

Tuning nonlinearity of the laser is the main source of deterioration of the spatial resolution in optical frequency-domain reflectometry (OFDR) system. In this paper, we develop methods for tuning nonlinearity correction in an OFDR system from the aspect of data acquisition and post-processing. An external clock based on a zero-crossing detection is researched and implemented using a customized circuit. Equal-spacing frequency sampling is, therefore, achieved in real-time. The zero-crossing detection for the beating frequency of 20 MHz is achieved. The maximum sensing distance can reach the same length of the auxiliary interferometer. Moreover, a nonlinearity correction method based on the self-reference method is proposed. The auxiliary interferometer is no longer necessary in this scheme. The tuning information of the laser is extracted by a strong reflectivity point at the end of the measured fiber. The tuning information is then used to resample the raw signal, and the nonlinearity correction can be achieved. The spatial resolution test and the distributed strain measurement test were both performed based on this nonlinearity correction method. The results validated the feasibility of the proposed method. This method reduces the hardware and data burden for the system and has potential value for system integration and miniaturization.