Velocity Sensor Research Articles

Analysis and suppression of the Rb resonance frequency error in NMR angular velocity sensor

The nuclear magnetic resonance (NMR) angular velocity sensor has the potential for high precision measurement in small volumes, which measures the 129Xe and 131Xe precession frequencies to obtain the angular velocity with respect to an inertial reference frame. One of the key challenges in frequency measurement is the long-term stability of the measured signal phase. The measured signal is acquired by applying a carrier magnetic field along the z-axis and demodulating the carrier signal at its frequency, which is typically fixed. However, fluctuations in light shifts and static magnetic fields can lead to instabilities in the Rb resonance frequency, consequently impacting the measurements of phase and precession frequencies of 129Xe and 131Xe. To address this issue, an analysis of the Rb resonance frequency error is conducted, and a suppression scheme based on carrier frequency correction is provided. This scheme can mitigate the effect of Rb resonance frequency fluctuations without further suppressing fluctuations of light shifts and static magnetic fields. The experiment demonstrates a 53.5 % reduction in the precession frequency error between 129Xe and 131Xe and a 59.0 % decrease in bias instability. This scheme can improve the long-term stability of 129Xe and 131Xe precession frequency measurements, thereby enhancing the performance of the NMR angular velocity sensor.

Piezoresistive snap-through detection for bifurcation-based MEMS sensors

We report on the piezoresistive method for detecting stability loss events in microelectromechanical sensors based on bifurcation. The method involves measuring the resistivity changes of an entire beam to detect snap-through transitions in an electrostatically actuated, bistable double-clamped crystalline silicon (Si) microbeam. The applicability of the suggested approach in two types of sensors—an ambient air temperature sensor or a mean air velocity sensor, is demonstrated. In both cases, the bistable beam, serving as the sensing element, is affected by the electrothermal Joule's heating and air cooling. The measured signal is obtained by monitoring the critical voltages of the snap-through transitions. Piezoresistive sensing is especially suitable for the response monitoring of the exposed to the environment, free-standing heated microbeam sensors, where optical, piezoelectric, or electrostatic interrogation methods are not applicable. The approach can be implemented in various bifurcation microsensors and for response monitoring of bistable actuators.

Vibration Reduction on Circular Disks with Vibroacoustic Metamaterials

Vibroacoustic metamaterials represent an innovative technology developed for broadband vibration reduction. They consist of an array of local resonators and are able to reduce vibrations over a wide frequency range, commonly referred to as a stop band. Vibroacoustic metamaterials may be a promising strategy to reduce out-of-plane vibrations of thin-walled, disk-shaped structures, such as saw blades. However, their behavior in rotating systems has not yet been fully understood. In this study, a vibroacoustic metamaterial integrated into a circular disk for the reduction of out-of-plane vibrations is experimentally investigated in the rotating and non-rotating state. Derived from the predominant frequency range of noise emitted by saw blades, a vibroacoustic metamaterial with a numerically predicted stop band in the frequency range from 2000 Hz to 3000 Hz, suitable for integration into a circular disk, is designed. The resonators of the metamaterial are realized by cutting slots into the disk using a waterjet cutting machine. To experimentally examine the structural dynamic behavior, the disk is excited by an impulse hammer and observed by a stationary optical velocity sensor on a rotor dynamics test stand. The results of the rotating and the non-rotating state are compared. The measurements are carried out at two different radii and at speeds up to 3000 rpm. A distinct stop band characteristic is shown in the desired frequency range from 2000 Hz to 3000 Hz in the rotating and non-rotating state. No significant shift of the stop band frequency range was observed during rotation. However, adjacent modes were observed to propagate into the stop band frequency range. This work contributes to a better understanding of the behavior of vibroacoustic metamaterials in the rotating state and enables future applications of vibroacoustic metamaterials for vibration reduction in rotating, disk-shaped structures such as saw blades, brake disks or gears.

Trajectory planning and control strategy optimization design of double electric cylinder erecting device

The transition of the rocket from a horizontal to an erect state before its launch on the offshore platform is a crucial stage. Compared with erecting the rocket on the ground, higher servo control and synchronization accuracy are required for erecting it on the offshore platform. Most rocket erecting devices on offshore platforms rely on hydraulic drive systems, posing challenges due to their lower servo control accuracy and difficulties in achieving high-precision synchronization. The erecting process, trajectory planning, control system, and control strategies of rockets driven by a double electric cylinder erecting device are studied, aiming at the requirement of erecting rocket devices on offshore platforms. This paper commences by establishing the kinematic model of erecting the rocket with a double electric cylinder erecting device. It delves into the process and trajectory of the erection rocket with a double electric cylinder erecting device. Subsequently, the focus shifts toward designing the control system, while inclination and angular velocity sensors monitor the erection process. Finally, designing and demonstrating control strategies for a double electric cylinder erecting device, three different control strategies, master control, master-slave control, and cross-coupling control, are analyzed, and the cross-coupling control strategy is selected as the control strategy of the double electric cylinder offshore platform rocket erecting device.

Potential for juvenile freshwater mussels to settle onto riverbeds from field investigation

Freshwater mussel populations have been declining at an alarming rate around the world. Herein, we investigate whether changing flow conditions, as they affect juvenile freshwater mussel settling, could be a potential causative factor for this decline in the Dan River, North Carolina, USA. We deployed two uplooking velocity sensors on the riverbed between May and November 2019: one where mussels reside and another where they do not. From this data, we calculated shear velocity, which is a measure of the turbulence that acts to lift particles into suspension and acts against particle settling. We determined that a shear velocity less than 0.66 cm/s would be required to settle relatively large and dense juvenile mussels onto the riverbed; however, the lowest shear velocity we measured was 0.9 cm/s. Additionally, we estimated that juvenile freshwater mussels as large as 280-510 µm could always be suspended and not be able to settle onto the riverbed at these two locations. Therefore, the flow during May-November 2019 was high enough to prohibit recruitment of juvenile freshwater mussels at the sensor locations. Furthermore, we have identified that the magnitude of the lowest flows has increased since 2000, which may be exacerbating the decline in freshwater mussels.

Nanowire sensor calibration and performance evaluation in microfluidic flow velocity monitoring

A microfluidic chip, integrated with a contact flow velocity sensor, was fabricated. A single gold nanowire prepared by nanoskiving was positioned across the bottom of a microfluidic channel. Real-time monitoring of the microfluidic flow velocity is achieved by leveraging the principle of forced heat exchange between the fluid and the solid nanowire. To harmonize theoretical calculations and experiments, leading to the derivation of a conversion formula between the flow equivalence factor and the flow velocity. Analysis of experimental data, specifically curves of resistance versus time, yields two characteristic parameters for the nanowire sensor: the step size of the flow equivalence factor and the resistivity variation. The performance of nanowire sensor was further analyzed by examining the patterns exhibited in the relationship between characteristic parameters (resolution and response characteristics) and both voltage and inlet flow rate. This work has potential applications in biomedical sensing, microfluidic mixing, and other areas where flow velocity control is required.

Flexible calorimetric flow sensor with unprecedented sensitivity and directional resolution for multiple flight parameter detection

The accurate perception of multiple flight parameters, such as the angle of attack, angle of sideslip, and airflow velocity, is essential for the flight control of micro air vehicles, which conventionally rely on arrays of pressure or airflow velocity sensors. Here, we present the estimation of multiple flight parameters using a single flexible calorimetric flow sensor featuring a sophisticated structural design with a suspended array of highly sensitive vanadium oxide thermistors. The proposed sensor achieves an unprecedented velocity resolution of 0.11 mm·s−1 and angular resolution of 0.1°. By attaching the sensor to a wing model, the angles of attack and slip were estimated simultaneously. The triaxial flight velocities and wing vibrations can also be estimated by sensing the relative airflow velocity due to its high sensitivity and fast response. Overall, the proposed sensor has many promising applications in weak airflow sensing and flight control of micro air vehicles.

Adaptive sensor fault tolerant control with prescribed performance for unmanned autonomous helicopter based on neural networks

PurposeThis paper aims to study a neural network-based fault-tolerant controller to improve the tracking control performance of an unmanned autonomous helicopter with system uncertainty, external disturbances and sensor faults, using the prescribed performance method.Design/methodology/approachTo ensure that the tracking error satisfies the prescribed performance, the authors adopt an error transformation function method. A control scheme based on the neural network and high-order disturbance observer is designed to guarantee the boundedness of the closed-loop system. A simulation is performed to prove the validity of the control scheme.FindingsThe developed adaptive fault-tolerant control method makes the system with sensor fault realize tracking control. The error transformation function method can effectively handle the prescribed performance requirements. Sensor fault can be regarded as a type of system uncertainty. The uncertainty can be approximated accurately using neural networks. A high-order disturbance observer can effectively suppress compound disturbances.Originality/valueThe tracking performance requirements of unmanned autonomous helicopter system are considered in the design of sensor fault-tolerant control. The inequality constraint that the output tracking error must satisfy is transformed into an unconstrained problem by introducing an error transformation function. The fault state of the velocity sensor is considered as the system uncertainty, and a neural network is used to approach the total uncertainty. Neural network estimation errors and external disturbances are treated as compound disturbances, and a high-order disturbance observer is constructed to compensate for them.

Design of a Vehicle Fatigue Driving Detection System Based on Multiple Signals

In recent years, traffic accidents have occurred frequently, and most of them are related to the level of fatigue of drivers. In order to avoid the dangers of fatigue driving, this article judges whether the driver is in a fatigued state by analyzing the changes in pressure, angle, and distance during driving, so as to remind the driver to reduce the probability of accidents. In terms of hardware, we use the AT89C51 microcontroller as the main control unit, and configure infrared sensors, ultrasonic sensors, angular velocity sensors, and pressure sensors to detect the physical state of the driver. In terms of software, we use C language to write code and optimize and compile it through Keil software. The system can display the detected data on the LCD display screen and send an alarm at the same time.

Research on high sensitivity optical fiber sensing method for simultaneous measurement of seawater velocity and temperature

Aiming at the need of high sensitivity flow velocity and temperature sensor in ocean research, an optical fiber sensor for the simultaneous measurement of seawater velocity and temperature was proposed by coupling a reflective Panda fiber polarization interferometer with a hollow cylindrical cantilever, which combining the stress sensitivity of Panda fiber and optical vernier effect to achieve simultaneous measurement and sensitization of flow velocity and temperature. Firstly, the theoretical formulas of velocity sensitivity and temperature sensitivity were obtained by theoretical derivation and finite element simulation. Secondly, a velocity and temperature measurement system was established experimentally, and the maximum velocity sensitivity was –233.86 nm/(m/s) at 0.42 m/s with the mean relative error compared with the theoretical sensitivity was 3.8 %, the maximum temperature sensitivity was −14.5 nm/(°C) with the mean relative error compared with the theoretical sensitivity was 8 %. Finally, nine different sets of seawater velocity and temperature were measured using the sensitivity matrix and compared with the Acoustic Doppler Velocimetry and Conductivity-Temperature-Depth meter, the mean relative error of velocity and temperature measurement results were 2.8 % and 2 %, respectively. The optical fiber sensor based on the cantilever is expected to play an important role in the field of ocean flow field measurement because of high sensitivity and the ability to measure velocity and temperature simultaneously.

Combined navigation system for substation inspection robot based on DGPS/DR multi-sensor fusion

To realize the routine inspection work of the capacitor tower inspection operation robot on the capacitor tower in the substation, and to guarantee the accuracy and safety of the robot’s movement in the substation, a multi-sensor combination navigation system and the corresponding Kalman fusion filter are designed. Combined with the overall structure of the substation and the working environment of the inspection robot, the navigation and positioning requirements of the robot are analyzed and compared, and the multi-sensor combination positioning technology using a combination of DGPS, attitude sensors and velocity sensors is determined. The Kalman fusion filter based on the constant velocity model is used to fuse the positioning information of multiple sensors, and more accurate and reliable navigation information is obtained compared with the single-sensor positioning system. According to the working environment of the substation, an outdoor planar robot mobile navigation experiment is carried out to collect the positioning information of multiple sensors and carry out data fusion processing to verify the accuracy and robustness of multi-sensor combination navigation and positioning.

Thermal Sensor of Groundwater Flow Velocity and Direction Measurement According to In Situ Monitoring of Thermal Conductivity and Dynamic Viscosity

Thermal Sensor of Groundwater Flow Velocity and Direction Measurement According to In Situ Monitoring of Thermal Conductivity and Dynamic Viscosity

Performance Improvement of Integrated MEMS Temperature, Humidity, and Air Velocity Sensors for Application in Smart Buildings

Performance Improvement of Integrated MEMS Temperature, Humidity, and Air Velocity Sensors for Application in Smart Buildings

Production of polyunsaturated fatty acids in pork backfat fermented by Mucor circinelloides

Pork backfat (PB) contains excessive saturated fatty acids (SFAs), but lacks polyunsaturated fatty acids (PUFAs). Excessive SFAs can be used as a substrate for the growth of certain microorganisms that convert them into PUFAs and monounsaturated fatty acids (MUFAs), and the added value of PB can be enhanced. In this study, Mucor circinelloides CBS 277.49 and Lactiplantacillus plantarum CGMCC 24189 were co-cultured for conversion of PB into fermented pork backfat (FPB) with high level of PUFAs. Our results showed that the content of γ-linolenic acid (GLA) and linoleic acid (LA) in the surface of FPB reached 9.04 ± 0.14 mg/g and 107.31 ± 5.16 mg/g for 7-day fermentation, respectively. To convert the internal SFAs of PB, ultrasound combined with papain was used to promote the penetrative growth of M. circinelloides into the internal PB, and the GLA level in the third layer of fat reached 2.58 ± 0.31 mg/g FPB. The internal growth of M. circinelloides in PB was promoted by adjusting the oxygen rate and ventilation rate through the wind velocity sensor. When the oxygen rate is 2 m/s and the ventilation rate is 18 m3/h, the GLA level in the third layer of fat reached 4.13 ± 1.01 mg/g FPB. To further improve the level of PUFAs in PB, FPB was produced by M. circinelloides at 18 °C. The GLA content on the surface of FPB reached 15.73 ± 1.13 mg/g FPB, and the GLA yield in the second and third layers of fat reached 8.68 ± 1.77 mg/g FPB and 6.13 ± 1.28 mg/g FPB, the LA yield in the second and third layers of fat reached 105.45 ± 5.01 mg/g FPB and 98.46 ± 4.14 mg/g FPB, respectively. These results suggested that excessive SFAs in PB can be converted into PUFAs and provided a new technique for improving PUFAs in FPB.Key points• This article achieved the conversion of PUFAs in pork backfat by Mucor circinelloides CBS 277.49 and Lactiplantacillus plantarum CGMCC 24189.• This article solved the internal growth of M. circinelloides CBS277.49 in pork backfat by ultrasound combined with papain.• This article proposed an innovative of promoting the internal growth of M. circinelloides and increasing the PUFAs production by oxygen ventilation in pork backfat.

Solution to the problem of detecting a malfunction of the position sensor of small spacecraft

The classic scheme for constructing a modern system for controlling the parameters of the angular motion of a spacecraft involves the use of high-precision gyroscopes, periodically adjusted according to the readings of optoelectronic devices. The most widely used in orientation and navigation systems are precision angular velocity sensors and gyroscopes on an electrostatic suspension, which determine the angles of rotation of the aircraft around its center of mass; Angular and linear accelerometers are also used, mounted in a certain way on the body of the aircraft.

Accelerate the numerical convergence of incompressible flows: Novel preconditioned characteristic boundary conditions

For the first time, the locally power-law preconditioning method (LPLPM) is used to formulate the preconditioned characteristic boundary conditions (CBCs). Then, it is implemented to solve the numerical modeling of unsteady and steady flows from viscous to turbulent regimes. The compatibility equations and Riemann invariants are mathematically derived and then utilized to the incompressible flow solvers as suitable boundary conditions. This method discretizes time derivative and governing equations' space terms by applying the four-stage, fourth-order Runge–Kutta method, and a finite volume, respectively. The preconditioning matrix in the LPLPM is automatically derived by local velocity sensors through a power-law formulation. The baseline k−ω is applied as an appropriate turbulence model. Several test cases are conducted around airfoils of Office National d'Etudes et de Recherches Aerospatiales, NACA0012 (National Advisory Committee for Aeronautics), and S809 at varied angles of attack of 0–20 and Reynolds numbers of 500 to 5.25 × 106 to examine the effectiveness and accuracy of the LPLPM employing preconditioned CBCs. A sensitivity analysis is also performed to examine how numerical parameters affect the simulation. The results show that using preconditioned CBCs in conjunction with LPLPM at the artificial boundary is precise, reliable, and computationally efficient in simulating viscous/turbulent flows. Furthermore, it is also concluded that the present approach considerably improves the convergence speed contrasted to the simplified boundary conditions.

A Multicore Fiber-Based Velocity Sensor

A Multicore Fiber-Based Velocity Sensor

Oceanographic dataset collected during the 2021 scientific expedition of the Canadian Coast Guard Ship Amundsen

Abstract. Since 2003, the state-of-the-art Canadian Coast Guard Ship (CCGS) research icebreaker Amundsen has furrowed the Canadian Arctic waters to support novel research endeavors and collect oceanographic data. This paper presents the data acquisition, the processing methods and an overview of the data collected during the 2021 expedition as the ship traveled over 30 000 km during 122 d across the Canadian Arctic Ocean, collecting sea surface, atmospheric and seabed underway measurements. A total of 266 casts of a conductivity, temperature and depth profiler mounted on a Conductivity Temperature Depth rosette (CTD Rosette) were also conducted to monitor the main physical, chemical and biological parameters of the water column. More specifically, the data presented here were collected with the CTD Rosette across historical sampling transects in Davis Strait, the North Water Polynya (NOW) and Cape Bathurst. A 182 km dedicated survey using the Moving Vessel Profiler® (MVP), equipped with CTD, transmissometer, dissolved oxygen, fluorescence and sound velocity sensors, was conducted across Hudson Strait. We also present an overview of the data collected by the underway systems (seabed, thermosalinograph and atmospheric). Such data are essential in understanding the impacts of climate warming on the unique environments of the Canadian Arctic Ocean. Amundsen Science supports and promotes easy access and sharing of such valuable data to the scientific community.

Evaluation of indicators of railway-induced annoying vibration based on building measurements developed by TOD: a discussion

The main negative impact of the residential buildings located on the cover structure of a Transit Oriented Development (TOD) metro depot is that residents would suffer from the train-induced annoying vibrations. Arguments accordingly arose on the possibility of evaluating indicators controversy for this application that acceleration data was more captured in the past while velocity would be more related to structure born noise. Therefore, this paper provided a relative comparison based on a measurement campaign that both velocity and acceleration sensors were installed together at the same time. The collected vibration accelerations and velocities are analyzed and discussed using the methods of transmission loss, coherence, and time and frequency domain analysis. The results indicated that even there was no difference for identifying the resonance frequency of structure, but the transit mobility and human annoyance evaluation were obviously different by using velocity or acceleration. Attempts to establish a relationship between the two indicators using the calculus method failed because they showed the largest error at the peak frequency at the same vibration level, which would have affected the evaluation results and the judgment on the choice of mitigation measures.

Online monitoring system of material moisture content based on the Kalman filter fusion algorithm in air-impingement dryer

A Kalman filter fusion algorithm was proposed, and an online monitoring system was developed for real-time monitoring of the moisture content of materials in an air-impingement dryer. The Kalman filter algorithm was used to estimate the optimal state of the original detection values of the weighting sensor and air velocity sensor. A backpropagation (BP) neural network fusion model was established, where the weight detection value, elastic substrate temperature, air velocity, and impingement distance were considered inputs and the real weight of the material was the output. The optimal topology of the BP neural network was selected, and the initial weights and thresholds of the BP neural network were optimized using a genetic algorithm. The coefficient of determination (R2) and root mean square error (RMSE) of the optimized BP neural network fusion model were 0.9995 and 4.9, respectively. The Kalman filter fusion algorithm, which can realize online monitoring of moisture content, was established using the Kalman filter algorithm and fusion model. Moreover, an online monitoring system for material moisture content was developed, validation experiments were carried out, and the R2 and RMSE of the nine sets of validation experiments were 0.9963 and 0.78, respectively. The monitoring system satisfied the requirements of material moisture content detection accuracy in the drying process. The developed monitoring system is greatly important for improving the automation level of the drying equipment for fruits and vegetables. The proposed Kalman filter fusion algorithm also provides a reference for other multifactor fusion detection.