High-accuracy fiber Bragg grating inclinometer.

Inclination monitoring plays a significant role in research on deformation monitoring of slopes, inclination monitoring of bridges, earthquake monitoring, and other areas of monitoring. Existing electromagnetic signal-based inclinometers face practical issues such as difficulty adapting to harsh environments, poor large-scale networking capabilities, and unstable signal transmission. Hence, what we believe to be a novel inclinometer based on fiber sensing principles is proposed. The sensor employs suspension sensing based on the plumb principle, using bearings to overcome mechanical friction caused by rigid fixation between the mass block and the cantilever, thereby improving sensitivity and accuracy of the sensor. Key structural parameters of the sensor were optimized and simulated, followed by fabrication of the sensor and performance test on an inclination test platform. Experimental results indicate that, within a measurement range of ±9∘, the sensor exhibited a sensitivity of 305.2 pm/°, a resolution of approximately 3.3×10-4 ∘, an accuracy of 2%, a repeatability error of 1.9%, and favorable creep resistance stability for long-term measurement, thus addressing the requirements for slope deformation monitoring.

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.

Miniaturized fiber Bragg grating accelerator sensors for low-frequency vibration monitoring.

Acceleration monitoring is an important technical means of seismic monitoring, oil exploration, deep well observation, etc. A miniaturized fiber Bragg grating (FBG) acceleration sensor with three cantilever beams is proposed against the fact that it is difficult for fiber-optic sensors to meet the requirements for low-frequency vibration monitoring. First, the model of the FBG acceleration sensor was built and theoretically analyzed; second, the effect of structural parameters on sensor sensitivity and natural frequency was analyzed, and the sensors were subjected to static stress analysis and modal simulation analysis through the ANSYS finite element analysis software; finally, the real sensors were developed and subjected to performance tests with a low-frequency vibration test system. According to the result, the natural frequency of the sensor is about 64 Hz, and its sensitivity is 201.3 pm/g; favorable linearity is observed at the working frequency band of 0.1-40 Hz, and the transverse interference is less than 2.51%. The research findings offer a reference for the development of like sensors and the further exploration of the lower limit of low frequency.

Research on a bimetallic-sensitized FBG temperature sensor.

Temperature measurement is of great significance for research in the health monitoring of large structures and earthquake precursors. Against the frequently reported low sensitivity of fiber Bragg grating (FBG) temperature sensors, a bimetallic-sensitized FBG temperature sensor was proposed. The sensitization structure of the FBG temperature sensor was designed, and the sensor sensitivity was analyzed; the lengths and materials of the substrate and strain transfer beam were analyzed theoretically; 7075 aluminum and 4J36 invar were chosen as bimetallic materials, and the ratio of the substrate length to the sensing fiber length was determined. The structural parameters were optimized; the real sensor was developed, and its performance was tested. The results suggested that the sensitivity of the FBG temperature sensor was 50.2 pm/°C, about five times than that of a bare FBG sensor, and its linearity was more than 0.99. The findings offer a reference for developing sensors of the same type and further improving the sensitivity of the FBG temperature sensors.

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.

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.

An efficient rotational direction heap-based optimization with orthogonal structure for medical diagnosis.

The heap-based optimizer (HBO) is an optimization method proposed in recent years that may face local stagnation problems and show slow convergence speed due to the lack of detailed analysis of optimal solutions and a comprehensive search. Therefore, to mitigate these drawbacks and strengthen the performance of the algorithm in the field of medical diagnosis, a new MGOHBO method is proposed by introducing the modified Rosenbrock's rotational direction method (MRM), an operator from the grey wolf optimizer (GWM), and an orthogonal learning strategy (OL). The MGOHBO is compared with eleven famous and improved optimizers on IEEE CEC 2017. The results on benchmark functions indicate that the boosted MGOHBO has several significant advantages in terms of convergence accuracy and speed of the process. Additionally, this article analyzed the diversity and balance of MGOHBO in detail. Finally, the proposed MGOHBO algorithm is utilized to optimize the kernel extreme learning machines (KELM), and a new MGOHBO-KELM is proposed. To validate the performance of MGOHBO-KELM, seven disease diagnostic questions were introduced for testing in this work. In contrast to advanced models such as HBO-KELM and BP, it can be concluded that the MGOHBO-KELM model can achieve optimal results, which also proves that it has practical significance in solving medical diagnosis problems.

Improved Resolution and Cost Performance of Low-Cost MEMS Seismic Sensor through Parallel Acquisition.

In earthquake monitoring, an important aspect of the operational effect of earthquake intensity rapid reporting and earthquake early warning networks depends on the density and performance of the deployed seismic sensors. To improve the resolution of seismic sensors as much as possible while keeping costs low, in this article the use of multiple low-cost and low-resolution digital MEMS accelerometers is proposed to increase the resolution through the correlation average method. In addition, a cost-effective MEMS seismic sensor is developed. With ARM and Linux embedded computer technology, this instrument can cyclically store the continuous collected data on a built-in large-capacity SD card for approximately 12 months. With its real-time seismic data processing algorithm, this instrument is able to automatically identify seismic events and calculate ground motion parameters. Moreover, the instrument is easy to install in a variety of ground or building conditions. The results show that the RMS noise of the instrument is reduced from 0.096 cm/s2 with a single MEMS accelerometer to 0.034 cm/s2 in a bandwidth of 0.1-20 Hz by using the correlation average method of eight low-cost MEMS accelerometers. The dynamic range reaches more than 90 dB, the amplitude-frequency response of its input and output within -3 dB is DC -80 Hz, and the linearity is better than 0.47%. In the records from our instrument, earthquakes with magnitudes between M2.2 and M5.1 and distances from the epicenter shorter than 200 km have a relatively high SNR, and are more visible than they were prior to the joint averaging.

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.

Design of a Low-Cost Small-Size Fluxgate Sensor.

Traditional fluxgate sensors used in geomagnetic field observations are large, costly, power-consuming and often limited in their use. Although the size of the micro-fluxgate sensors has been significantly reduced, their performance, including indicators such as accuracy and signal-to-noise, does not meet observational requirements. To address these problems, a new race-track type probe is designed based on a magnetic core made of a Co-based amorphous ribbon. The size of this single-component probe is only Φ10 mm × 30 mm. The signal processing circuit is also optimized. The whole size of the sensor integrated with probes and data acquisition module is Φ70 mm × 100 mm. Compared with traditional fluxgate and micro-fluxgate sensors, the designed sensor is compact and provides excellent performance equal to traditional fluxgate sensors with good linearity and RMS noise of less than 0.1 nT. From operational tests, the results are in good agreement with those from a standard fluxgate magnetometer. Being more suitable for modern dense deployment of geomagnetic observations, this small-size fluxgate sensor offers promising research applications at lower costs.

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.