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In order to solve the problem of flexible sliding tactile composite sensing in the actual grasp of intelligent robot fingers, this paper proposes a research on a convex fiber grating tactile sliding sensor based on mechanical fingers. Based on the sensing principle of fiber Bragg grating, 3D printing technology was used to encapsulate the FBG sensor array with elastic 50 A resin, a double-layer "hemispherical cuboid" distributed sensing unit was designed, and the FBG slippery tactile sensor was actually pasted on the surface of the mechanical finger for static and dynamic experiments. The experimental results show that the slippery tactile sensor designed in this paper has a good linear relationship with temperature and strain. The temperature sensitivities of the polymer-packaged FBGs are KT1 = 13.04 pm/°C and KT2 = 12.91 pm/°C, and they have a pressure sensitivity of 40.4 pm/N and 31.2 pm/N, respectively. The FBG sliding tactile sensor not only realizes the identification of the sliding signal generation point and the end point but also completes the classification and identification of sandpaper, cardboard, and polypropylene plastic, and it has a high degree of fit with the robot finger, which has certain application value for the intelligent robot sliding tactile signal perception.
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The in-situ health condition of carbon fiber reinforced polymer (CFRP) reinforced structures has become an important topic, which can reflect the structural performance of the retrofitted structures and judge the design theory. An optical fiber-based structural health monitoring technique is thus suggested. To check the effectiveness of the proposed method, experimental testing on smart CFRP reinforced steel beams under impact action has been performed, and the dynamic response of the structure has been measured by the packaged FBG sensors attached to the surface of the beam and the FBG sensors inserted in the CFRP plates. Time and frequency domain analysis has been conducted to check the structural feature of the structures and the performance of the installed sensors. Results indicate that the packaged Fiber Bragg Grating (FBG) sensors show better sensing performance than the bare FBG sensors in perceiving the impact response of the beam. The sensors embedded in the CFRP plate show good measurement accuracy in sensing the external excitation and can replace the surface-attached FBG sensors. The dynamic performance of the reinforced structures subjected to the impact action can be straightforwardly read from the signals of FBG sensors. The larger impact energies bring about stronger impact signals.
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Body temperature provides an insight into the physiological state of a person, and body temperature changes reflect much information about human health. In this study, a garment for monitoring human body temperature based on fiber Bragg grating (FBG) sensors is reported. The FBG sensor was encapsulated with a PMMA tube and calibrated in the thermostatic water bath. The results showed that FBG sensors had good vibration resistance, and the wavelength changed about 0-1 pm at a 0.5-80 Hz vibration frequency. The bending path of the optical fiber after integration with clothing is discussed. When the bending radius is equal to or greater than 20 mm, a lower bending loss can be achieved even under the bending and stretching of the human body. The FBG sensor, the optical fiber, and the garment were integrated together using hot melt glue by the electric iron and the hot press machine. Through experiments of monitoring human body temperature, the sensor can reach the human armpit temperature in about 10-15 min with the upper arm close to the torso. Because it is immune to electromagnetic interferences, the smart garment can be used in some special environments such as ultrasonography, magnetic resonance (MR), and aerospace.
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Temperatura Corporal , Tecnología de Fibra Óptica , Vestuario , Tecnología de Fibra Óptica/métodos , Cuerpo Humano , Humanos , Fibras ÓpticasRESUMEN
The use of fiber Bragg grating (FBG) sensors is proposed to solve the technical problem of poor sensor stability in the long-term safety monitoring of shaft lining structures. The auxiliary shaft of the Zhuxianzhuang coal mine was considered as the engineering background, and a test system implementing FBG sensors was established to monitor the long-term safety of the shaft lining structure. Indoor simulation testing revealed that the coefficient of determination (r2) between the test curves of the FBG sensor and the resistance strain gauge is greater than 0.99 in both the transverse and vertical strains. Therefore, the FBG sensor and resistance strain gauge test values are similar, and the error is small. The early warning value was obtained by calculation, according to the specific engineering geological conditions and shaft lining structure. The monitoring data obtained for the shaft lining at three test levels over more than three years reveal that the measured vertical strain value is less than the warning value, indicating that the shaft lining structure is currently in a safe state. The analysis of the monitoring data reveals that the vertical strain increment caused by the vertical additional force is approximately 0.0752 µÎµ/d. As the mine drainage progresses, the increasing vertical additional force acting on the shaft lining will compromise the safety of the shaft lining structure. Therefore, the monitoring must be enhanced to facilitate decision-making for safe shaft operation.
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Tecnología de Fibra Óptica , Fibras Ópticas , Monitoreo FisiológicoRESUMEN
The paper explores the possibility of using high-resolution fiber Bragg grating (FBG) sensing technology for on-specimen strain measurement in the laboratory. The approach provides a means to assess the surface deformation of the specimen, both the axial and radial, through a chain of FBG sensor (C-FBG), in a basic setup of a uniaxial compression test. The method is cost-effective, straightforward and can be commercialized. Two C-FBG; one was applied directly to the sample (FBGBare), and the other was packaged (FBGPack) for ease of application. The approach measures the local strain with high-resolution and accuracy levels that match up to the existing local strain measuring sensors. The approach enables the evaluation of small-strain properties of the specimen intelligently. The finite element model analysis deployed has proven the adaptability of the technique for measuring material deformation. The adhesive thickness and packaging technique have been shown to influence the sensitivity of the FBG sensors. Owing to the relative ease and low-cost of instrumentation, the suggested method has a great potential to be routinely applied for elemental testing in the laboratory.
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This study investigated the reflected spectral deformation mechanism of fiber Bragg grating (FBG) sensors with crack propagation. This analysis was performed based on the simulated FBG response by applying modified-transfer matrix modeling (TMM) with the strain states, which were extracted by the finite element method (FEM) analysis. Experimental data were obtained from FBG sensors bonded in an aluminum alloy structure and subjected to multiple crack lengths, and the strain values were obtained by digital image correlation (DIC) technology. Based on the simulations and the experimental full spectral response, we compared the performance of two damage features: The full width at half maximum (FWHM) and the spectral difference. In addition, results showed that the two features were insensitive to experimental noise and were highly sensitive to the complex strain field caused by crack propagation. Moreover, the damage features changes in the crack propagation process also provided a way for crack position measurement. Ultimately, the 10 mm grating lengths sensors showed better performance to the crack detection with longer sensitivity distance. According to the research in this paper, the crack position was quantitatively determined by evaluating different damage features of the reflected spectrum.
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In this paper, a new damage feature, spectral area, was extracted to effectively detect crack location by studying the deformation mechanism of fiber Bragg grating (FBG) reflection spectra. In order to verify the robustness and reliability of spectral area to detect crack location, the following work was carried out: Firstly, the strain information was extracted by extended finite element method (XFEM) with fatigue crack propagation. The transmission matrix method (TMM) was used to simulate FBG reflection spectra using numerical results. Secondly, the fatigue crack growth monitoring experiment based on FBG sensors was carried out, and the digital image correlation (DIC) method was used to measure the strain values at the placement of FBG sensors with crack propagation. The temperature characteristic test of FBG was carried out to investigate the influence of temperature variation on the spectral area. The results presented that the spectral area was insensitive to temperature variation and experimental noise, and was greatly sensitive to the complex non-uniform strain field cause by crack damage. Moreover, compared with the 5 mm FBG sensor, the 10 mm FBG sensor showed a larger critical detection range for crack damage. Therefore, the spectral area can be used as a reliable damage feature to detect the crack location quantitatively based on the simulated and experimental results.
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In this article, we present a novel stochastic algorithm called simultaneous sensor calibration and deformation estimation (SCADE) to address the problem of modeling deformation behavior of a generic continuum manipulator (CM) in free and obstructed environments. In SCADE, using a novel mathematical formulation, we introduce a priori model-independent filtering algorithm to fuse the continuous and inaccurate measurements of an embedded sensor (e.g., magnetic or piezoelectric sensors) with an intermittent but accurate data of an external imaging system (e.g., optical trackers or cameras). The main motivation of this article is the crucial need of obtaining an accurate shape/position estimation of a CM utilized in a surgical intervention. In these robotic procedures, the CM is typically equipped with an embedded sensing unit (ESU) while an external imaging modality (e.g., ultrasound or a fluoroscopy machine) is also available in the surgical site. The results of two different set of prior experiments in free and obstructed environments were used to evaluate the efficacy of SCADE algorithm. The experiments were performed with a CM specifically designed for orthopaedic interventions equipped with an inaccurate Fiber Bragg Grating (FBG) ESU and overhead camera. The results demonstrated the successful performance of the SCADE algorithm in simultaneous estimation of unknown deformation behavior of the utilized unmodeled CM together with realizing the time-varying drift of the poor-calibrated FBG sensing unit. Moreover, the results showed the phenomenal out-performance of the SCADE algorithm in estimation of the CM's tip position as compared to FBG-based position estimations.
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We have determined the sensitivity and detection limit of a new fiber Bragg grating (FBG)-based optoelectronic micro-indenter for biomechanical testing of cartilage and compared the results to indentation-type atomic force microscopy (IT-AFM) and histological staining. As test samples, we used bovine articular cartilage, which was enzymatically degraded ex vivo for five minutes using different concentrations of collagenase (5, 50, 100 and 500 µg/mL) to mimic moderate extracellular matrix deterioration seen in early-stage osteoarthritis (OA). Picrosirius Red staining and polarization microscopy demonstrated gradual, concentration-dependent disorganization of the collagen fibrillar network in the superficial zone of the explants. Osteoarthritis Research Society International (OARSI) grading of histopathological changes did not discriminate between undigested and enzymatically degraded explants. IT-AFM was the most sensitive method for detecting minute changes in cartilage biomechanics induced by the lowest collagenase concentration, however, it did not distinguish different levels of cartilage degeneration for collagenase concentrations higher than 5 µg/mL. The FBG micro-indenter provided a better and more precise assessment of the level of cartilage degeneration than the OARSI histological grading system but it was less sensitive at detecting mechanical changes than IT-AFM. The FBG-sensor allowed us to observe differences in cartilage biomechanics for collagenase concentrations of 100 and 500 µg/mL. Our results confirm that the FBG sensor is capable of detecting small changes in articular cartilage stiffness, which may be associated with initial cartilage degeneration caused by early OA.
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Enfermedades de los Cartílagos/diagnóstico , Cartílago Articular/química , Elasticidad , Osteoartritis/diagnóstico , Animales , Fenómenos Biomecánicos , Enfermedades de los Cartílagos/patología , Cartílago Articular/fisiología , Bovinos , Colagenasas , Microscopía de Fuerza Atómica , Osteoartritis/patologíaRESUMEN
We propose a peak seeking algorithm to extract the damage characteristic-variation of central wavelength to monitor the crack damage status in aluminum alloy plates using surface bonded fiber Bragg grating (FBG) sensors. The FBG sensors are sensitive to the uniform and non-uniform strain distribution along their longitudinal direction, and the effect appears in the power spectrum of the reflected light from the gauge section. In this paper, we propose a fast-self-adaptive multi-peak seeking algorithm to detect the central wavelength shifting of the FBG reflection spectrum with the crack propagation. The proposed peak searching algorithm results point to a significant improvement compared to other conventional methods. Then the central wavelength shifting is applied to explain the crack propagation behavior of the aluminum plates under quasi-static tensile test conditions. The different damages feature changing intervals which are associated with the crack position and the FBGs location, demonstrating that central wavelength shifting performs as an indicator to detect structural crack damage.
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A combined sensor to simultaneously measure strain, vibration, and temperature has been developed. The sensor is composed of two Fiber Bragg gratings (FBGs) and a vibration gainer. One FBG is used to measure strain, while the other measures vibration and temperature. The gainer has a mass block which is used to increase its sensitivity to vibration. The main beam of the vibration gainer was designed as a trapezoid in order to reduce the strain gradient while sensing vibration. In addition, an interrogation method was used to eliminate interactions between measured parameters. Experiments were carried out to analyze the performance of the proposed sensor. For individual strain measurement in the range of 0-152 µÎµ, the sensitivity and nonlinearity error were 1.878 pm/µÎµ and 2.43% Full Scale (F.S.), respectively. For individual temperature measurement in the range of 50-210 °C, the sensitivity and nonlinearity error were 29.324 pm/°C and 1.88% F.S., respectively. The proposed sensor also demonstrated a sensitivity of 0.769 pm/m·s-2 and nonlinearity error of 1.83% F.S. for vibration measurement in the range of 10-55 m/s2. Finally, simultaneously measuring strain, temperature, and vibration resulted in nonlinearity errors of 4.23% F.S., 1.89% F.S., and 2.23% F.S., respectively.
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As the applications of fiber Bragg gratings (FBGs) continue to grow and become more advanced, it becomes necessary to understand their behavior when exposed to high temperatures in unique situations. In these experiments, uniform 1530-nm fiber Bragg gratings and Type K Cr-Al thermocouples were embedded in three-ply carbon fiber composites. A 100 W high energy laser (HEL) heated the composites to high temperatures over timespans less than one second, and FBG spectral data and thermocouple temperature data were collected during each HEL heating test. The data from three high energy laser tests that represent different levels of damage to the FBG are analyzed to explore the spectral response and thermal decay of embedded FBG sensors when exposed to high temperatures over short timespans. Results are compared to a previously proposed power-law model describing the decay of FBGs in bare fiber when held at constant temperatures over much longer timespans.
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This research focuses on a desensitization method to develop a wide-range FBG sensor for extra-large strain monitoring, which is an essential requirement in large scale infrastructures or for some special occasions. Under appropriate hypotheses, the strain transfer distribution of wide-range FBG sensor based on the shear-lag theory is conducted to improve the accuracy of extra-large strain measurements. It is also discussed how the elastic modulus of adhesive layer affects the strain transfer rate. Two prototypes in different monitoring ranges are designed and fabricated by two layers of steel pipe encapsulation. The presented theoretical model is verified by experimental results. Moreover, it is demonstrated that experimentation in regards to the calibration of the wide-range FBG sensor, improved the amplification coefficient up to 2.08 times and 3.88 times, respectively. The static errors are both calculated and analyzed in this experiment. The wide-range FBG strain sensor shows favourable linearity and stability, which is an excellent property of sensors for extra-large strain monitoring.
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For high-speed trains, out-of-roundness (OOR)/defects on wheel tread with small radius deviation may suffice to give rise to severe damage on both vehicle components and track structure when they run at high speeds. It is thus highly desirable to detect the defects in a timely manner and then conduct wheel re-profiling for the defective wheels. This paper presents a wayside fiber Bragg grating (FBG)-based wheel condition monitoring system which can detect wheel tread defects online during train passage. A defect identification algorithm is developed to identify potential wheel defects with the monitoring data of rail strain response collected by the devised system. In view that minor wheel defects can only generate anomalies with low amplitude compared with the wheel load effect, advanced signal processing methods are needed to extract the defect-sensitive feature from the monitoring data. This paper explores a Bayesian blind source separation (BSS) method to decompose the rail response signal and to obtain the component that contains defect-sensitive features. After that, the potential defects are identified by analyzing anomalies in the time history based on the Chauvenet's criterion. To verify the proposed defect detection method, a blind test is conducted using a new train equipped with defective wheels. The results show that all the defects are identified and they concur well with offline wheel radius deviation measurement results. Minor defects with a radius deviation of only 0.06 mm are successfully detected.
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With the development in the exploitation of maritime resources, the structural health monitoring (SHM) of offshore structures becomes necessary. This study focuses on addressing the practical issues of application of fiber Bragg grating (FBG) sensors for the SHM of offshore structures, in particular an FPSO (floating, production, storage, and offloading unit) vessel. Due to the harsh marine environment and tough working conditions, the FBG sensors must have sufficient protection and good repeatability for long-term monitoring. Thorough research has been conducted to identify the most suitable, commercially available protection packaging for FBG sensors for offshore applications. Further, the performance of the selected FBG sensor packaging is tested under conditions of strong sunlight, heavy rain, and salty water in order to emulate the marine environment. Moreover, the installation method of the packaged FBG sensors is equally important, as it ensures the repeatability and durability of the sensors for their long-term performance. It is shown that the packaged FBG sensors can be installed using resin-based epoxy to maintain the repeatability of the sensor over the long-term. Further, the packaged FBG sensors are installed and tested on a simple FPSO model. The experimental results under full load and ballast draft conditions show that the proposed FBG sensors are competent for the SHM of offshore structures.
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A combined stress-vibration sensor was developed to measure stress and vibration simultaneously based on fiber Bragg grating (FBG) technology. The sensor is composed of two FBGs and a stainless steel plate with a special design. The two FBGs sense vibration and stress and the sensor can realize temperature compensation by itself. The stainless steel plate can significantly increase sensitivity of vibration measurement. Theoretical analysis and Finite Element Method (FEM) were used to analyze the sensor's working mechanism. As demonstrated with analysis, the obtained sensor has working range of 0-6000 Hz for vibration sensing and 0-100 MPa for stress sensing, respectively. The corresponding sensitivity for vibration is 0.46 pm/g and the resulted stress sensitivity is 5.94 pm/MPa, while the nonlinearity error for vibration and stress measurement is 0.77% and 1.02%, respectively. Compared to general FBGs, the vibration sensitivity of this sensor is 26.2 times higher. Therefore, the developed sensor can be used to concurrently detect vibration and stress. As this sensor has height of 1 mm and weight of 1.15 g, it is beneficial for minimization and integration.
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In this paper, a fiber Bragg grating (FBG)-based stress monitoring system instrumented on an orthotropic steel deck arch bridge is demonstrated. The FBG sensors are installed at two types of critical fatigue-prone welded joints to measure the strain and temperature signals. A total of 64 FBG sensors are deployed around the rib-to-deck and rib-to-diagram areas at the mid-span and quarter-span of the investigated orthotropic steel bridge. The local stress behaviors caused by the highway loading and temperature effect during the construction and operation periods are presented with the aid of a wavelet multi-resolution analysis approach. In addition, the multi-modal characteristic of the rainflow counted stress spectrum is modeled by the method of finite mixture distribution together with a genetic algorithm (GA)-based parameter estimation approach. The optimal probability distribution of the stress spectrum is determined by use of Bayesian information criterion (BIC). Furthermore, the hot spot stress of the welded joint is calculated by an extrapolation method recommended in the specification of International Institute of Welding (IIW). The stochastic characteristic of stress concentration factor (SCF) of the concerned welded joint is addressed. The proposed FBG-based stress monitoring system and probabilistic stress evaluation methods can provide an effective tool for structural monitoring and condition assessment of orthotropic steel bridges.
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FBG sensors offer many advantages, such as a lack of sensitivity to electromagnetic waves, small size, high durability, and high sensitivity. However, their maximum strain measurement range is lower than the yield strain range (about 1.0%) of steel strands when embedded in steel strands. This study proposes a new FBG sensing technique in which an FBG sensor is recoated with polyimide and protected by a polyimide tube in an effort to enhance the maximum strain measurement range of FBG sensors embedded in strands. The validation test results showed that the proposed FBG sensing technique has a maximum strain measurement range of 1.73% on average, which is 1.73 times higher than the yield strain of the strands. It was confirmed that recoating the FBG sensor with polyimide and protecting the FBG sensor using a polyimide tube could effectively enhance the maximum strain measurement range of FBG sensors embedded in strands.
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Monitoring of roof activity is a primary measure adopted in the prevention of roof collapse accidents and functions to optimize and support the design of roadways in underground coalmines. However, traditional monitoring measures, such as using mechanical extensometers or electronic gauges, either require arduous underground labor or cannot function properly in the harsh underground environment. Therefore, in this paper, in order to break through this technological barrier, a novel monitoring system for roof safety control in underground coal mining, using fiber Bragg grating (FBG) material as a perceived element and transmission medium, has been developed. Compared with traditional monitoring equipment, the developed, novel monitoring system has the advantages of providing accurate, reliable, and continuous online monitoring of roof activities in underground coal mining. This is expected to further enable the prevention of catastrophic roof collapse accidents. The system has been successfully implemented at a deep hazardous roadway in Zhuji Coal Mine, China. Monitoring results from the study site have demonstrated the advantages of FBG-based sensors over traditional monitoring approaches. The dynamic impacts of progressive face advance on roof displacement and stress have been accurately captured by the novel roadway roof activity and safety monitoring system, which provided essential references for roadway support and design of the mine.
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This paper presents a novel framework for probabilistic crack size quantification using fiber Bragg grating (FBG) sensors. The key idea is to use a high-order extended finite element method (XFEM) together with a transfer (T)-matrix method to analyze the reflection intensity spectra of FBG sensors, for various crack sizes. Compared with the standard FEM, the XFEM offers two superior capabilities: (i) a more accurate representation of fields in the vicinity of the crack tip singularity and (ii) alleviation of the need for costly re-meshing as the crack size changes. Apart from the classical four-term asymptotic enrichment functions in XFEM, we also propose to incorporate higher-order functions, aiming to further improve the accuracy of strain fields upon which the reflection intensity spectra are based. The wavelength of the reflection intensity spectra is extracted as a damage sensitive quantity, and a baseline model with five parameters is established to quantify its correlation with the crack size. In order to test the feasibility of the predictive model, we design FBG sensor-based experiments to detect fatigue crack growth in structures. Furthermore, a Bayesian method is proposed to update the parameters of the baseline model using only a few available experimental data points (wavelength versus crack size) measured by one of the FBG sensors and an optical microscope, respectively. Given the remaining data points of wavelengths, even measured by FBG sensors at different positions, the updated model is shown to give crack size predictions that match well with the experimental observations.