High-precision Sensor Research Articles

High-Precision Laser Self-Mixing Displacement Sensor Based on Orthogonal Signal Phase Multiplication Technique

A new signal processing method named orthogonal signal phase multiplication (OSPM) is proposed, which is used to improve the precision of vibration measurement in a phase-modulating self-mixing interferometer (SMI). The modulated signal is acquired by an electro-optic modulator, which is placed in the external cavity. Higher measurement precision is realized by performing the phase multiplication algorithm on the orthogonal signals extracted from the harmonic components of the signal spectrum. Theoretically, the displacement reconstruction precision of OSPM is higher than that of conventional modulation methods, and it can be continuously improved by increasing the multiplication times. The feasibility and performance of the proposed method are verified by simulated signals and confirmed by experiments; the absolute error is less than 11 nm, and relative error is less than 0.75%, within the amplitude range from 661 nm to 2013 nm. This method does not involve additional optical elements, and its effectiveness meet the requirements for real-time high-precision measurements.

Acquisition approach of moment of inertia based on brushless DC torque motor

In order to meet the requirements of the small moment of inertia of the brushless DC torque motor, the optimal design of the shafting and the research on the measurement method were carried out on the basis of the structure of the flat motor rotor and the high-precision sensor. In this paper, ProE5.0 software is used to model and simulate the shaft structure of the permanent magnet synchronous motor. After comparing the common measurement methods of the moment of inertia, the single-wire torsional oscillation method is used to test and verify the moment of inertia of typical structural parts. The moment of inertia of the motor rotor is simulated and identified by the speed jammer identification algorithm.The test results show that the identification error of the constructed identification algorithm is less than 5% for the moment of inertia identification. After the brushless DC torque motor is assembled, the method can be used as a verification method for the parameters of the moment of inertia, which has strong practical significance.

Mechanical analysis of the improved superelastic Ni-Ti alloy wire using the orthodontic simulator with high-precision sensors

PurposeThe authors have been using improved superelastic Nickel-Titanium alloy wire (ISW) to close and align extraction spaces simultaneously, instead of separately using rigid wires for closing extraction spaces and Ni–Ti alloy wires for leveling and aligning. ISW has a low stiffness, which makes it challenging to generate sufficient moments. This study aimed to demonstrate the forces and moments exerted on adjacent brackets using an orthodontic simulator (OSIM) attached to a high-precision 6-axis sensor. Materials and methodsIn experiment 1, a 0.016 × 0.022-inch ISW, stainless steel (SS) wire, and β-titanium wires were ligatured into the two brackets. The 0.018 × 0.025-inch slot self-ligating brackets were bonded to two simulated teeth at the same height, and the experiment was conducted using the high-precision OSIM. The distance between the brackets was 10 mm, the V-bend angles of the installed wires were 10°, 20°, 30°, and 40°, and the apex position was set at the center of the bracket. In experiment 2, 6.0- and 9.0-mm long elastomeric chains were placed on the same brackets as in Experiment 1 to measure forces and moments. The distance between the brackets was increased by 1.0 mm from 6.0 to 15.0 mm. Both experiments were conducted in a 37 °C thermostatic chamber similar to the oral environment. Results and discussionIn experiment 1, we measured moments on both sides for all the wires. As the V-bend angle increased, the absolute values of the moments also increased. With a V-bend angle of 10°, there was a significant (p < 0.05) difference in the moment generated in the left and right brackets among the three wire types. In the ISW, −1.67 ± 0.38 N・mm was generated in the left bracket, while 0.38 ± 0.26 N・mm was generated in the right bracket at 10°. At 20°, −1.77 ± 0.69 N・mm was generated in the left bracket, while 2.37 ± 0.94 N・mm was generated in the right bracket. At 30°, −2.98 ± 0.49 N・mm was generated in the left bracket, while 3.25 ± 0.32 N・mm was generated in the right bracket. Moreover, at 40°, −3.96 ± 0.58 N・mm was generated in the left bracket, while 3.55 ± 0.53 N・mm was generated in the right bracket. Furthermore, in experiment 2, the moments increased in proportion to the increase in distance between the centers of the two brackets. Absolute values of the moments were approximately equal for the left and right brackets. The 6.0-mm elastomeric chain generated a minimum force of −0.09 ± 0.05 N in the left direction when the distance between brackets was 6.0 mm, while a maximum of 1.24 ± 0.3 N when the distance between brackets was 12 mm in the right bracket. In the left bracket, minimum and maximum forces of −0.09 ± 0.07 and 1.3 ± 0.4 N were generated in the right direction, respectively. The 9.0-mm elastomeric chain generated a minimum force of 0.03 ± 0.07 N in the left direction when the distance between brackets was 9.0 mm, while a maximum of 1.3 ± 0.1 N when the distance between brackets was 15 mm in the right bracket. In the left bracket, minimum and maximum forces of 0.05 ± 0.06 and 0.98 ± 0.2 N were generated in the right direction, respectively. ConclusionMechanical data of the ISW have been collected in the study, which was previously difficult to perform owing to the low stiffness of the wire. It is suggested that the ISW can provide sufficient moments with the addition of V-bends to close the space by bodily movement.

Broadband transverse unidirectional scattering and large range nanoscale displacement measuring based on the interaction between a tightly focused azimuthally polarized beam and a silicon hollow nanostructure.

We theoretically propose a broadband transverse unidirectional scattering scheme based on the interaction between a tightly focused azimuthally polarized beam (APB) and a silicon hollow nanostructure. When the nanostructure is located at a specific position in the focal plane of the APB, the transverse scattering fields can be decomposed into contributions from transverse components of the electric dipoles, longitudinal components of magnetic dipoles and magnetic quadrupole components. In order to satisfy the transverse Kerker conditions for these multipoles within a wide infrared spectrum, we design a novel nanostructure with hollow parallelepiped shape. Through numerical simulations and theoretical calculations, this scheme exhibits efficient transverse unidirectional scattering effects in the wavelength range of 1440 nm to 1820 nm (380 nm). In addition, by adjusting the position of the nanostructure on the x-axis, efficient nanoscale displacement sensing with large measuring ranges can be achieved. After analyses, the results prove that our research may have potential applications in the field of high-precision on-chip displacement sensors.

AN EXPERIMENTAL STUDY ON ADDED MASS COEFFICIENT OF VORTEX-INDUCED VIBRATION OF A CIRCULAR CYLINDER

In this paper, an experiment study with aspect ratio 100 of a circular cylinder was conducted in a wave-current channel. The FBG sensors were attached on the circular cylinder which are used to capture vibration signal, two high-precision bellows type sensors were used to monitor fluctuant support force, and the dynamic response of circular cylinder was finally calculated by modal analysis method. The effect of flow velocity, mass ratio and top tension of circular cylinder on the amplitude ratio, frequency ratio and added mass coefficient was evaluated. The results showed that top tension had a greater influence on the amplitude; the added mass coefficient demonstrated a nonlinear relationship with external flow velocity. The added mass coefficient decreases when the reduced velocity increases. At a particular reduced velocity, the added mass coefficient decreases when the top tension increases or mass ratio increases.

A high-speed 13-bit two-step single-slope ADC for large array CMOS image sensors

This paper proposes a 13-bit two-step single-slope (TS-SS) ADC for high-speed CMOS image sensors. The ADC design method is based on the ideas of time sharing and time compression, moves the fine conversion time to the coarse conversion time period, and eliminates the traditional method's time redundancy issue. The differential nonlinearity (DNL) and integral nonlinearity (INL) are simulated to be +0.8/-0.8 LSB and +2.1/-3.5 LSB, respectively, for the 55 nm 1P4M CMOS process. 512 ns is the conversion time of the 13-bit ADC. The power consumption is 47 μW, and the effective number of bits (ENOB) is 11.33 bits. In comparison to existing advanced ADCs, the method proposed in this paper can increase the ADC conversion rate by more than 60% while maintaining low power consumption and high precision, thereby providing theoretical support for the readout and conversion of high-speed and high-precision CMOS image sensors.

Cross-calibration method based on an automated observation site.

Cross-calibration methods are widely used in high-precision remote sensor calibrations and ensure observational consistency between sensors. Because two sensors must be observed under the same or similar conditions, the cross-calibration frequency is greatly reduced; performing cross-calibrations on Aqua/Terra MODIS, Sentinel-2A/Sentinel-2B MSI and other similar sensors is difficult due to synchronous-observation limitations. Additionally, few studies have cross-calibrated water-vapor-observation bands sensitive to atmospheric changes. In recent years, standard automated observation sites and unified processing technology networks, such as an Automated Radiative Calibration Network (RadCalNet) and an automated vicarious calibration system (AVCS), have provided automatic observation data and means for independently, continuously monitoring sensors, thus offering new cross-calibration references and bridges. We propose an AVCS-based cross-calibration method. By limiting the observational-condition differences when two remote sensors transit over wide temporal ranges through AVCS observation data, we improve the cross-calibration opportunity. Thereby, cross-calibrations and observation consistency evaluations between the abovementioned instruments are realized. The influence of AVCS-measurement uncertainties on the cross-calibration is analyzed. The consistency between the MODIS cross-calibration and sensor observation is within 3% (5% in SWIR bands); that for the MSI is within 1% (2.2% in the water-vapor-observation band); and for the cross-calibration of Aqua MODIS and the two MSI, the consistency between the cross-calibration-predicted TOA reflectance and the sensor-measured TOA reflectance was within 3.8%. Thus, the absolute AVCS-measurement uncertainty is also reduced, especially in the water-vapor-observation band. This method can be applied to cross-calibrations and measurement consistency evaluations of other remote sensors. Later, the spectral-difference influences on cross-calibrations will be further studied.

Neural Shape-From-Shading for Survey-Scale Self-Consistent Bathymetry From Sidescan

Sidescan sonar is a small and cost-effective sensing solution that can be easily mounted on most vessels. Historically, it has been used to produce high-definition acoustical images that experts may use to identify targets on the seafloor or in the water column. While solutions have been proposed to produce bathymetry solely from sidescan, or in conjunction with multibeam, they have had limited impact. This is partly a result of mostly being limited to single survey lines. In this article, we propose a modern, scalable solution to create high quality survey-scale bathymetry from many sidescan survey lines. By incorporating multiple observations of the same place, results can be improved as the estimates reinforce each other. Our method is based on <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">sinusoidal representation networks</i> , a recent advance in neural representation learning. We demonstrate the scalability of the approach by producing bathymetry from a large sidescan survey. The resulting quality is demonstrated by comparing to data collected with a high-precision multibeam sensor.

A high-precision silicon-on-insulator position sensor

Integrated photonic devices provide significant advantages over their conventional counterparts, such as a drastically reduced footprint as well as compatibility with other photonic or electronic circuitry. In this work, we present a high-precision optical position sensor fabricated on a silicon-on-insulator platform. The sensor relies on the principle of position-dependent directional waveguide coupling upon excitation of a monolithically integrated scatterer with a tightly focused polarization-tailored beam. We demonstrate a spatial resolution of 7.2 nm, corresponding to approximately λ/200.

A High-Precision and Low-Power Capacitive Pressure Sensor Interface IC With Wireless Power and Data Transfer for a Pressure Sensor Implant

This article presents a system-on-a-chip (SoC) for pressure sensors in 180-nm CMOS technology. It can interface with a capacitive pressure sensor with an inductive wireless power supply and data transmission via load-shift keying (LSK). It integrates an analog front end (AFE), bandgap references (BGRs), delta-sigma ADC, I2C, RC oscillator, low-dropout regulators (LDOs), shorting control switches, and full-bridge rectifier (Rct). An external coil receives wireless power, which is rectified and regulated to 1.8 V by the full-bridge Rct and LDOs. The AFE samples the capacitance change of the pressure sensor to a voltage that is converted into 19-bit digital data by the delta-sigma ADC, which is then converted into 43 Hz per sample serial data by the I2C block. A temperature sensor is included, and 19-bit measurements are transmitted in serial with capacitance data. Serial data are transmitted wirelessly using LSK. This SoC has a measured accuracy of 1 mmHg between 575- and 900-mmHg absolute with a wireless power supply and wireless data transfer.

Delay-Sensitive Energy-Efficient UAV Crowdsensing by Deep Reinforcement Learning

Mobile crowdsensing (MCS) by unmanned aerial vehicles (UAVs) servicing delay-sensitive applications becomes popular by navigating a group of UAVs to take advantage of their equipped high-precision sensors and durability for data collection in harsh environments. In this paper, we aim to simultaneously maximize collected data amount, geographical fairness, and minimize the energy consumption of all UAVs, as well as to guarantee the data freshness by setting a deadline in each timeslot. Specifically, we propose a centralized control, distributed execution framework by decentralized deep reinforcement learning (DRL) for delay-sensitive and energy-efficient UAV crowdsensing, called DRL-eFresh. It includes a synchronous computational architecture with GRU sequential modeling to generate multi-UAV navigation decisions. Also, we derive an optimal time allocation solution for data collection while considering all UAV efforts and avoiding much data dropout due to limited data upload time and wireless data rate. Simulation results show that DRL-eFresh significantly improves the energy efficiency, as compared to the best baseline DPPO, by 14% and 22% on average when varying different sensing ranges and number of PoIs, respectively.

In-situ observation of seabed vertical deformation in Yellow River Delta under storm surges

Sediment destruction poses a major risk to marine engineering facilities in river delta areas. The vertical deformation of seabed induced by storm surges is one of the major causes of sediment destruction. In this study, an in-situ observation system for monitoring the seabed vertical deformation was developed. The system includes a Paroscienctific high-precision water pressure sensor, a tide & wave recorder, and an Acoustic Doppler Current Profiler (ADCP). A processing method of the high-precision water pressure data was established. The advantage of this data processing method is that it allows us to obtain the water depth variation in shallow sea area based on the observed water pressure data. The system and the processing method were applied in an in-situ observation, which was carried out in Chengdao Sea area in the Yellow River Delta from December 2020 to January 2021. During this observation, marine hydrodynamic changes and vertical deformation of seabed were synchronously monitored. Three storm surge events were observed during this period. The vertical deformation process of seabed during the storm surges was quantitatively analyzed. After the first two storm surge events, the monitored vertical settlement of seabed reached 8.97 mm. A seabed vertical deformation mechanism was established based on the in-situ monitoring data.

First-Principles Calculation of the Temperature-Dependent Transition Energies in Spin Defects.

Spin qubits associated with color centers are promising platforms for various quantum technologies. However, to be deployed in robust quantum devices, the variations of their intrinsic properties with the external conditions, in particular temperature and strain, should be known with high precision. Unfortunately, a predictive theory on the temperature dependence of the resonance frequency of electron and nuclear spin defects in solids remains lacking. In this work, we develop a first-principles method for the temperature dependence of the zero-field splitting, hyperfine interaction, and nuclear quadrupole interaction of color centers. As a testbed, we compare our ab initio calculations with experiments for the nitrogen-vacancy (NV-) center in diamond, finding good agreements. We identify the major origin of the temperature dependence as a second-order effect of dynamic phonon vibrations, instead of the thermal-expansion strain. The method can be applied to different color centers and provides a theoretical tool for designing high-precision quantum sensors.

High-precision micro-displacement measurement in a modified reversal shearing interferometer using vortex beams

We propose a novel micro-displacement measurement system that employs a modified reversal shearing interference structure based on vortex beam interference. The micro-displacement in the measurement path caused a change in the light path and resulted in an optical path difference (OPD) between the reference and measurement paths. This OPD led to the rotation of the petal-like pattern obtained by the interference between two paths. The rotation angle of the petal-like pattern was proportional to the OPD caused by micro-displacement. We used the virtual phase-shifting method to extract the helical phase front, and the Radon transform to measure the angle of the helical phase front. We achieved a high-accuracy micro-displacement measurement with a measurement error of less than 0.067 nm when using a vortex beam with a topological charge of six. This system has an extremely simple structure and is easy to adjust. It is of great significance to the miniaturized design of high-precision displacement sensors.

Dual-Phase Inspired Soft Electronic Sensors with Programmable and Tunable Mechanical Properties.

Wearable and stretchable sensors are important components to strictly monitor the behavior and health of humans and attract extensive attention. However, traditional sensors are designed with pure horseshoes or chiral metamaterials, which restrict the biological tissue engineer applications due to their narrow regulation ranges of the elastic modulus and the poorly adjustable Poisson's ratio. Inspired by the biological spiral microstructure, a dual-phase metamaterial (chiral-horseshoes) is designed and fabricated in this work, which possesses wide and programmable mechanical properties by tailoring the geometrical parameters. Experimental, numerical, and theoretical studies are conducted, which reveal that the designed microstructures can reproduce mechanical properties of most natural animals such as frogs, snakes, and rabbits skin. Furthermore, a flexible strain sensor with the gauge factor reaching 2 under 35% strain is fabricated, which indicates that the dual-phase metamaterials have a stable monitoring ability and can be potentially applied in the electronic skin. Finally, the flexible strain sensor is attached on the human skin, and it can successfully monitor the physiological behavior signals under various actions. In addition, the dual-phase metamaterial could combine with artificial intelligence algorithms to fabricate a flexible stretchable display. The dual-phase metamaterial with negative Poisson's ratio could decrease the lateral shrinkage and image distortion during the stretching process. This study offers a strategy for designing the flexible strain sensors with programmable, tunable mechanical properties, and the fabricated soft and high-precision wearable strain sensor can accurately monitor the skin signals under different human motions and potentially be applied for flexible display.

Fatigue monitoring of coated steel belts by means of magnetic inspection

Coated steel belts (CSBs) are the primary load-bearing components of elevators. As a result, they may experience severe fatigue failure during their long-term service. In this study, a flexible fatigue fixture for CSBs is designed to simulate the CSB fatigue damage process for implementing a tensile fatigue test. The magnetic induction intensity signal on the surface of the CSB in a geomagnetic field environment is recorded using a high-precision weak magnetic sensor. Moreover, the CSB fatigue damage process is monitored online via the acquired magnetic induction intensity value. The fatigue test results indicate the following: the variation in the magnetic induction intensity signal curve can reflect the entire fatigue failure process when the CSB is under stress; the fatigue failure process of the steel wire inside the CSB does not occur smoothly as its progress occurs in stages; and the variation trend in the residual value between the magnetic induction intensity and fitting curves effectively indicates the degree of fatigue damage caused to the CSB.

Research and Practice on Slope Monitoring of Power Grid Construction Based on IoT Technology

In order to solve the shortcomings of traditional slope monitoring technology in automation, timeliness, and intelligence, this paper studies a slope monitoring system for high slopes in power grid construction based on power Internet of Things technology with characteristics of comprehensive perception, reliable delivery, and convenient application. By applying high-precision sensors, the plane and elevation monitoring accuracy of the system can reach a millimeter level. The layout principle of digital slope monitoring sensors is summarized and proposed according to traditional slope monitoring data in a power grid construction project in order to solve the relationship between actual slope monitoring demand and equipment investment. The slope monitoring system is applied in the three-level slope of a pilot project, and this technology realizes real-time judgment, efficient data transmission, and processing, making the obtained slope stability information more comprehensive, dynamic, and reliable.

Position Self-Correction of Resolver Based on a Composite Method in Gimbal System

This article explores a composite self-correction method for the angular position of the resolver in the gimbal system of the control moment gyroscope (CMG). The nonideal signals of the resolver in the gimbal resolver-to-digital conversion (RDC) system result in a systematic error, which can decrease the performance of the output torque of the CMG. However, it is impractical to adopt additional high-precision sensors to correct the angular position of the resolver in the installed gimbal system on account of the limitation of the structure and space. Therefore, a novel self-correction composite method based on a discrete extended state observer (DESO) and a harmonic observer method (HOM) is put forward to calibrate the angular position of the resolver. First, the sine and cosine signals with harmonics can be directly obtained. Then, the composite proposed method is performed to get the accurate angular position of the resolver, and the position error can also be acquired. Based on the position error, the compensation table can be established, and finally, the high-precision position can be acquired. The proposed self-correction method is verified by simulation and experiments, and the results show that the angular position accuracy is significantly improved.

High-Precision 3D Reconstruction Study with Emphasis on Refractive Calibration of GelStereo-Type Sensors.

GelStereo sensing technology is capable of performing three-dimensional (3D) contact shape measurement under various contact structures such as bionic curved surfaces, which has promising advantages in the field of visuotactile sensing. However, due to multi-medium ray refraction in the imaging system, robust and high-precision tactile 3D reconstruction remains a challenging problem for GelStereo-type sensors with different structures. In this paper, we first propose a universal Refractive Stereo Ray Tracing (RSRT) model for GelStereo-type sensing systems to realize 3D reconstruction of the contact surface. Moreover, a relative geometry-based optimization method is presented to calibrate multiple parameters of the proposed RSRT model, such as the refractive indices and structural dimensions. Furthermore, extensive quantitative calibration experiments are performed on four different GelStereo sensing platforms; the experimental results show that the proposed calibration pipeline can achieve less than 0.35 mm in Euclidean distance error, based on which we believe that the proposed refractive calibration method can be further applied in more complex GelStereo-type and other similar visuotactile sensing systems. Such high-precision visuotactile sensors can facilitate the study of robotic dexterous manipulation.

Pred-SF: A Precipitation Prediction Model Based on Deep Neural Networks.

How to predict precipitation accurately and efficiently is the key and difficult problem in the field of weather forecasting. At present, we can obtain accurate meteorological data through many high-precision weather sensors and use them to forecast precipitation. However, the common numerical weather forecasting methods and radar echo extrapolation methods have insurmountable defects. Based on some common characteristics of meteorological data, this paper proposes a Pred-SF model for precipitation prediction in target areas. The model focuses on the combination of multiple meteorological modal data to carry out self-cyclic prediction and a step-by-step prediction structure. The model divides the precipitation prediction into two steps. In the first step, the spatial encoding structure and PredRNN-V2 network are used to construct the autoregressive spatio-temporal prediction network for the multi-modal data, and the preliminary predicted value of the multi-modal data is generated frame by frame. In the second step, the spatial information fusion network is used to further extract and fuse the spatial characteristics of the preliminary predicted value and, finally, output the predicted precipitation value of the target region. In this paper, ERA5 multi-meteorological mode data and GPM precipitation measurement data are used for testing to predict the continuous precipitation of a specific area for 4 h. The experimental results show that Pred-SF has strong precipitation prediction ability. Some comparative experiments were also set up for comparison to demonstrate the advantages of the combined prediction method of multi-modal data and the stepwise prediction method of Pred-SF.