2502 OFDRによるひずみ分布計測の測定範囲の拡張に関する考察(J10-1 計測・モニタリング・解析(1),J10 知的材料・構造システム)

In this paper, one large Fiber Bragg Grating (FBG) sensor sensing network for bridge local health monitoring was studied, designed and implemented to Harbin Sifangtai Bridge, China. According to the hot point principle and finite element analysis results, FBG sensors installation scheme was made to monitor the local strain of key elements, respectively. 60 FBG sensors had been installed in monitoring points along the height of I-shape girders distributed in three main monitoring sections along the bridge. Monitoring results in load testing period was obtained, the static and dynamic results show that FBG sensors can monitoring the local strain precisely, and the local strain response is in the safe range under test vehicle load. Monitoring results in service period was obtained, 9 months after load test. Results show that maximum local strain responses in three main monitoring sections are in the safe range, under the dynamic vehicle load. Comparison of the monitoring results from FBG sensor sensing network are used to unveil the local health condition of Sifangtai Bridge reflected by local strain response.

Performance assessment of discrete wavelet transform for de-noising of FBG sensors signals embedded in asphalt pavement

Multivariate statistics based damage detection algorithms employed in conjunction with novel sensing technologies are attracting more attention for long term Structural Health Monitoring of civil infrastructure. In this study, two practical data driven methods are investigated utilizing strain data captured from a 4-span bridge model by Fiber Bragg Grating (FBG) sensors as part of a bridge health monitoring study. The most common and critical bridge damage scenarios were simulated on the representative bridge model equipped with FBG sensors. A high speed FBG interrogator system is developed by the authors to collect the strain responses under moving vehicle loads using FBG sensors. Two data driven methods, Moving Principal Component Analysis (MPCA) and Moving Cross Correlation Analysis (MCCA), are coded and implemented to handle and process the large amount of data. The efficiency of the SHM system with FBG sensors, MPCA and MCCA methods for detecting and localizing damage is explored with several experiments. Based on the findings presented in this paper, the MPCA and MCCA coupled with FBG sensors can be deemed to deliver promising results to detect both local and global damage implemented on the bridge structure.

Fiber Bragg grating (FBG) sensors were used to measure the torsional strain distribution in a second-generation (rare-earth) Ba2Cu3Oy high-temperature superconducting sample tape (SST) at 77 K. Two SST samples were prepared. A slit was fabricated in each sample to allow an optical fiber to be embedded. In the first sample, a 10-mm-long single grating element was inserted into the slit. In the second sample, three grating elements of 10-mm length each were put into the slit. These grating elements were fabricated along a single-mode fiber and could be addressed individually using the wavelength division multiplexing (WDM) technique. Finally, the samples were recoated with a primary and secondary coating to form an embedded sensing system. When the high-temperature superconducting (HTS) tape is subjected to torsion, there is a strain induced in the FBG sensor, which varies the grating period accordingly. It was interrogated using a tunable laser in a WDM scheme. Based on the wavelength shift and the photoelastic properties of the FBG sensor embedded to the HTS tape, the torsional deformation of the HTS tape can be obtained. In this paper, the design and technology requirements to embed the single and WDM FBG sensors into the coated conductors are presented. Initial experiments to measure the torsional strain distribution at 77 K are reported.

Fiber Bragg Grating (FBG) sensor is a new type of optical sensor that is light in quality, small in volume, easy to achieve distributed measurement, and easy to embed. When FBG sensor technology is introduced to the damage detection of the CFRP shaft, the shortcomings of conventional damage detection technologies, including ultrasonic testing and radiographic testing, can be effectively overcome. Considering the working load, operating environment and life requirements of the CFRP shaft , combined with the relevant national and industry standards for composite material testing, Prepare three CFRP shaft with embedded fiber gratings (non-destructive CFRP shaft, single hole CFRP shaft , double hole CFRP shaft), the hole diameter is 1mm, and the layering of CFRP shaft is ([0 / 90 / 45 / 0 / 0 / 45 / -45 / 0 / -45 / 0 / 90 / 90 / 0 / -45 / 0 / -45 / 45 / 0 / 0 / 45 / 90 / 0 ]). FBG is embedded between 18 and 19 layers, pasted on the surface of CFRP shaft with 10 FBG sensors (named FBG1, FBG2... FBG10). The strain information of the CFRP shaft is obtained through fiber grating to obtain the deformation of the CFRP shaft under a three-point bending load. Each CFRP shaft is loaded 12 times (A1, A2, A3, B1, B2, B3, C1, C2, C3, D1, D2, D3). Through the BP neural network method, the mapping relationship between strain distribution and damage model was established. In the model, the FBG sensor measures the strain of the CFRP shaft and forms the input of the neural network. Combined with the damage situation of the composite material, the learning samples of the network formed. After learning and training, the neural network can damage recognition. To better verify the accuracy of the neural network to distinguish and identify the CFRP shaft non-destructive, single-hole, and double-hole damage patterns. The finite element analysis was used to simulate the damage of three CFRP shafts under the same experimental conditions, and extract the eigenvalues at the same position to form the input of the network, combined with the damage situation of the composite material, constitutes a learning sample of the network. The experiment shows that the CFRP shaft experiment based on BP neural network verifies the reliability of the CFRP shaft damage recognition method. The finite element analysis is used to extract the strain information of CFRP shaft measuring points with different damage modes. The damage position information and strain information were input into the BP neural network. The experimental results are in good agreement with the simulation results, which verifies the accuracy of the BP neural network to distinguish the CFRP shaft non-destructive, single-hole, and doublehole damage patterns.

Embedded fiber Bragg grating (FBG) sensors are attractive for in-situ structural monitoring, especially in fiber reinforced composites. Their implementation in metallic structures is hindered by the thermal limit of the protective coating, typically a polymer material. The purpose of this study is to demonstrate the embedding of FBG sensors into metals with the ultimate objective of using FBG sensors for structural health monitoring of metallic structures. To that end, ultrasonic additive manufacturing (UAM) is utilized. UAM is a solid-state manufacturing process based on ultrasonic metal welding that allows for layered addition of metallic foils without melting. Embedding FBGs through UAM is shown to result in total cross-sectional encapsulation of the sensors within the metal matrix, which encourages uniform strain transfer. Since the UAM process takes place at essentially room temperature, the industry standard acrylate protective coating can be used rather than requiring a new coating applied to the FBGs prior to embedment. Measurements presented in this paper show that UAM-embedded FBG sensors accurately track strain at temperatures higher than 400 °C. The data reveals the conditions under which detrimental wavelength hopping takes place due to non-uniformity of the load transferred to the FBG. Further, optical cross-sectioning of the test specimens shows inhibition of the thermal degradation of the protective coating. It is hypothesized that the lack of an atmosphere around the fully-encapsulated FBGs makes it possible to operate the sensors at temperatures well above what has been possible until now. Embedded FBGs were shown to retain their coatings when subjected to a thermal loading that would result in over 50 percent degradation (by volume and mass) in atmospherically exposed fiber.

Fiber Bragg Grating (FBG) sensors are comprehensively recognized as a structural stability monitoring device for all kinds of geo-materials by either embedding into or bonding onto the structural entities. The physical model in geotechnical engineering, which could accurately simulate the construction processes and the effects on the stability of underground caverns on the basis of satisfying the similarity principles, is an actual physical entity. Using a physical model test of underground caverns in Shuangjiangkou Hydropower Station, FBG sensors were used to determine how to model the small displacements of some key monitoring points in the large-scale physical model during excavation. In the process of building the test specimen, it is most successful to embed FBG sensors in the physical model through making an opening and adding some quick-set silicon. The experimental results show that the FBG sensor has higher measuring accuracy than other conventional sensors like electrical resistance strain gages and extensometers. The experimental results are also in good agreement with the numerical simulation results. In conclusion, FBG sensors could effectively measure small displacements of monitoring points in the whole process of the physical model test. The experimental results reveal the deformation and failure characteristics of the surrounding rock mass and make some guidance for the in situ engineering construction.

As an important factor in-service Structure health monitoring (SHM), predictions of displacement become the basis for determining the decrease of modern aircraft and aerospace structural performance. Optical fiber Bragg grating (FBG) sensors are considered an important tool for SHM , however, FBG sensors are rarely directly applied to monitor the displacement because of the intrinsic fragility. To overcome such a problem, we propose a novel method for design and curving an FBG sensor using auxiliary flexible driving function of the shape memory alloy (SMA) to monitor the displacement. The FBG sensor is curved slowly to an S shape along with SMA wire. Strain gradient of SMA which is applied by displacement loading is obtained by finite element analysis. By analyzing the spectral simulations, bandwidth of spectrum is increased and the central wavelength is changed. Spectral properties of curved FBG sensor are analyzed by stretch experiments, the results shown that its bandwidth, light intensity of peak and central wavelength are increased and the central wavelength change is linear with displacement. A new sensor based on an FBG sensor and SMA Actuators can be used to monitor displacement with displacement sensitivity of 141pm/mm.

Fiber Bragg grating sensors for in-situ temperature measurement on bending a flexible planar supercapacitor

Composite structures with embedded fiber optic sensors: A smart propellant tank for future spacecraft applications

The article describes process of implementation of optical Fiber Bragg Grating (FBG) sensors into the composite wing structure and their behavior during the strength test. The wing is of all-composite construction. The upper and lower skins are made of glass/epoxy composite. The spar caps are made of carbon/epoxy unidirectional composite. Optical fibers were integrated directly into the spar caps and into the adhesive joints. They were oriented in parallel with the main spar axis. The first optical fiber with chain of multiple FBG sensors was integrated into the structure of upper spar cap. Another FBG chain of FBG sensors was located in the adhesive joint of lower spar cap and shear web. The wing was instrumented with strain gages as well. Strain gages were glued to the sides of the spar caps. Static load was produced by a hydraulic actuator. Experimental results from strain gages and FBG sensors were compared with the results of the analytical analysis of the wing.

Fiber Bragg grating (FBG) sensors are excellent transducers for collecting ultrasonic wave signals for structural health monitoring (SHM). Typically, FBG sensors are directly bonded to the surface of a structure to detect signals. Unfortunately, demodulating relevant information from the collected signal demands a high signal-to-noise ratio because the structural ultrasonic waves have low amplitudes. Our previous experimental work demonstrated that the optical fiber could be bonded at a distance away from the FBG location, referred to here as remote bonding. This remote bonding technique increased the output signal amplitude compared to the direct bonding case, however the mechanism causing the increase was not explored. In this work, we simulate the previous experimental work through transient analysis based on the finite element method, and the output FBG response is calculated through the transfer matrix method. The model is first constructed without an adhesive to assume an ideal bonding condition, investigating the difference in excitation signal coherence along the FBG length between the two bonding configurations. A second model is constructed with an adhesive to investigate the effect of the presence of the adhesive around the FBG. The results demonstrate that the amplitude increase is originated not from the excitation signal coherence, but from the shear lag effect which causes immature signal amplitude development in the direct bonding case compared to the remote bonding case. The results also indicate that depending on the adhesive properties the surface-bonded optical fiber manifests varying resonant frequency, therefore resulting in a peak amplitude response when the input excitation frequency is matched. This work provides beneficial reference for selecting adhesive and calibrating sensing system for maximum ultrasonic detection sensitivity using the FBG sensor.

This paper proposes multipoint optical fiber sensing system based on fiber Bragg grating (FBG) sensor array. The low reflectivity FBG sensors having the same Bragg wavelength are connected cascaded in the same fiber line as the sensing elements of optical fiber sensing system. This can increase the monitoring points and reduce manufacturing costs of FBG sensor. To verify the effectiveness, the system simulator based on equivalent circuit model by microwave technology was developed. Simulation result shows that though multi-reflections can be caused by FBG sensors with the same Bragg wavelength connected cascaded in the same line, the effect may become weak as reflectivity of FBG sensors are reduced to 0.02.

Thermal modeling of the power transformer to estimate the internal temperature only reflects the winding hot spot to a certain extent. The application of optical fiber sensors to measure transformer internal temperature directly can obtain the true temperature with high accuracy and stability and overcome the shortcomings of traditional electric sensors. This paper analyses the measuring principle of FBG (Fiber Bragg Grating) sensor, and constructs transformer internal temperature measurement platform with FBG temperature sensors, then adopt short-circuit method to simulate the process of winding heat under different load conditions. Finally the measurement of transformer internal temperature is conducted respectively with FBG temperature sensors and thermocouples. Comparison and analysis of the results shows that FBG sensors can effectively measure the internal temperature of the transformer.

The effectiveness of monitoring systems for composite materials is improving owing to their increasing utilisation. Abrupt failure in composite requires an effective detection method and monitoring system. The fibre Bragg grating (FBG) sensor is one of the alternative sensors used for detecting and monitoring the structural health of an engineering structure. This study evaluated the applicability of the FBG sensor for fatigue damage monitoring in the composite. This study involved composite fabrication and experimental work. The glass fibre reinforced polymer specimens were fabricated using fibre glass and resin and made into flat workpieces. The workpieces were then utilised in a series of fatigue tests. Prior to the fatigue test, tensile tests were conducted to verify the ultimate strength of the material. Commencement of fatigue tests were recorded using the FBG sensor. Once the tests were started, the signals were acquired using the FBG sensor simultaneously. Data acquisition was continued during the fatigue test progression until the specimen failed. Results show the FBG wavelength shifted from its original position during tension loading and whenever the composite was released to its original position in the cyclic test. The FBG sensor seems a promising way to monitor fatigue damage and can be utilised in fatigue monitoring. Its wavelength shifts or changes is capable to monitor fatigue damage progression effectively.