Cross spring leaf-based high-sensitivity low-frequency dual-FBG acceleration sensor.

The measurement of low-frequency vibration signals is of great significance in seismic monitoring, health monitoring of large and medium-sized engineering structures, and resource exploration. In view of the low sensitivity of fiber Bragg grating (FBG) acceleration sensors in measuring low-frequency vibration signals, a high-sensitivity, low-frequency dual-FBG acceleration sensor is proposed. Theoretical formula derivation and ANSYS software were used to optimize the design and simulation analysis of the structural parameters of the sensor. The real sensor was made based on the simulation results, and a test system was established to test its performance. According to the findings, the natural frequency of the acceleration sensor is 65 Hz. It gives a flat sensitivity response in the low frequency band of 3-45 Hz. The dynamic range is 92.63 dB at 10 Hz, the acceleration sensitivity is 1498.29 pm/g, and the linearity R2 is 0.9998. The relative standard deviation of the sensor repeatability is 1.75%, and the transverse crosstalk in the working frequency band is -33.99dB. Designed with a high sensitivity and excellent temperature compensation capacity in the low-frequency band, the designed sensor is suitable for low- and medium-frequency vibration detection in engineering.

Research on sensitized Fiber Bragg Grating temperature sensor based on bimetal three-substrates.

Temperature is one of the most important physical quantities in the field of earthquake precursor observation. Aiming at the problem of low sensitivity in the Fiber Bragg Grating (FBG) temperature sensor, the sensitized FBG temperature sensor based on bimetal three-substrates is proposed. Through theoretical analysis of the bimetallic model, the structural parameters of the sensor are optimized, and the sensor is simulated and analyzed with ANSYS. Then, the sensor is developed according to the simulation results, and the temperature test system is built to test the performance of the sensor. The results show that the sensitivity of the temperature sensor is 49.3 pm/°C, which is about 4.9 times that of the bare FBG sensor, and the linearity is over 0.999. The research results provide a reference for developing the same type of sensors and further improving the sensitivity of FBG temperature sensors.

A new L-shaped rigid beam FBG acceleration sensor.

Acceleration detection is an important technology in the fields of seismic monitoring, structural health monitoring and resource exploration. A FBG acceleration sensor with the combination of L-shaped rigid beam and spring structure based on bearings is proposed against the low sensitivity that predominates in the low-frequency vibration measurement by FBG acceleration sensors, where L-shaped rigid beam is utilized to amplify the vibration signal, and is fixed by the bearings at both ends to effectively suppress the transverse crosstalk. The effects of structural parameters on the sensitivity and natural frequency of the sensors were analyzed using Origin theory, and such parameters were optimized; next, static stress and modal simulation analysis was made using COMSOL; in the end, a test system was built to test the performance of the real sensors. According to the findings, the acceleration sensor, whose natural frequency is 57 Hz, is of a flat sensitivity response in the low frequency range of 1-35 Hz, with the dynamic range being 89.83 dB, the acceleration sensitivity being up to 1241.85 pm/g, the coefficient of determination R2 for the sensitivity fit is 0.9997, and the transverse crosstalk being -26.20 dB within the operating frequency band. The findings offer a reference for improving the low-frequency vibration measurement capability of FBG acceleration sensors.

Structural analysis and optimization design of mechanical pendulum of differential capacitance seismometer.

Seismometers can collect and record earthquake information in real time, and they play an important role in earthquake prediction and post-earthquake monitoring. Aiming at the high natural frequency problem of the mechanical pendulum of differential capacitance seismometers, this study employed the ANSYS simulation software to establish a finite element model of the mechanical pendulum; using the constructed model, this study performed static and modal analysis on the key structure, the cross reed, and conducted topological optimization on the shape of the reed. Moreover, the sine calibration method was adopted to measure the natural frequency of the mechanical pendulum before and after optimization, and the experimental results showed that after optimization, the natural frequency of the mechanical pendulum had been reduced by 22%, decreasing from 5.4 to 4.2 Hz, which proved the feasibility of the optimization design.

Hinge-type FBG acceleration sensor based on double elastic plate.

It is critical for the health monitoring of large-scale structures such as bridge, railway and tunnel to acquire the medium-frequency and high-frequency vibration signals. To solve the problems of low sensitivity and poor transverse anti-interference of the medium-frequency and high-frequency fiber acceleration sensor, a hinge-type Fiber Bragg Grating(FBG) acceleration sensor based on double elastic plate has been proposed, and the hinge and elastic plate are used as elastomer to realize the miniaturization and transverse interference suppression of the sensor. The MATLAB and the ANSYS are used for theoretical analysis and optimization of sensor sensitivity and resonance frequency, structural static stress analysis and modal simulation analysis, while the test system is built to test the sensor performance. The results show that the resonance frequency of the sensor is 1300 Hz; the sensor has a flat sensitivity response in the middle-high frequency band of 200-800 Hz; the sensitivity is about 20 pm/g, and the fiber central wavelength drift and acceleration have good linearity and stability, while the transverse anti-interference is about 3.16%, which provides a new idea for monitoring of medium-frequency and high-frequency vibration signals in large-scale structures.

A multi-cantilever beam low-frequency FBG acceleration sensor.

The acquisition of 2-50 Hz low-frequency vibration signals is of great significance for the monitoring researches on engineering seismology, bridges & dams, oil & gas exploration, etc. A multi-cantilever beam low-frequency FBG acceleration sensor is proposed against the low sensitivity that predominates in the low-frequency vibration measurement by FBG acceleration sensors. Structural parameters of the sensor is subjected to simulation analysis and optimization design using the ANSYS software; the real sensor is developed based on the simulation results in the following manner: Three rectangular of the cantilever beams are evenly arranged around the mass block at 120°to improve the sensitivity and alleviate the transverse crosstalk of sensor; in the end, a performance test is performed on the sensor. According to the research findings, the sensor, whose natural frequency is approximately 64 Hz, is applicable for monitoring the low-frequency vibration signals within the range 16-54 Hz. The sensor sensitivity is approximately [Formula: see text], the linearity being greater than 99%, the transverse interference immunity being lower than 2.58%, and the dynamic range being up to 86 dB. The findings offer a reference for developing sensor of the same type and further improving the sensitivity of fiber optic acceleration sensor.

Estimation of stress distribution in ferromagnetic tensile specimens using low cost eddy current stress measurement system and BP neural network.

Estimation of the stress distribution in ferromagnetic components is very important for evaluating the working status of mechanical equipment and implementing preventive maintenance. Eddy current testing technology is a promising method in this field because of its advantages of safety, no need of coupling agent, etc. In order to reduce the cost of eddy current stress measurement system, and obtain the stress distribution in ferromagnetic materials without scanning, a low cost eddy current stress measurement system based on Archimedes spiral planar coil was established, and a method based on BP neural network to obtain the stress distribution using the stress of several discrete test points was proposed. To verify the performance of the developed test system and the validity of the proposed method, experiment was implemented using structural steel (Q235) specimens. Standard curves of sensors at each test point were achieved, the calibrated data were used to establish the BP neural network model for approximating the stress variation on the specimen surface, and the stress distribution curve of the specimen was obtained by interpolating with the established model. The results show that there is a good linear relationship between the change of signal modulus and the stress in most elastic range of the specimen, and the established system can detect the change in stress with a theoretical average sensitivity of -0.4228 mV/MPa. The obtained stress distribution curve is well consonant with the theoretical analysis result. At last, possible causes and improving methods of problems appeared in the results were discussed. This research has important significance for reducing the cost of eddy current stress measurement system, and advancing the engineering application of eddy current stress testing.