Distributed Pressure Sensors Research Articles

Minimalist Design for Multi-Dimensional Pressure-Sensing and Feedback Glove with Variable Perception Communication

Immersive human–machine interaction relies on comprehensive sensing and feedback systems, which enable transmission of multiple pieces of information. However, the integration of increasing numbers of feedback actuators and sensors causes a severe issue in terms of system complexity. In this work, we propose a pressure-sensing and feedback glove that enables multi-dimensional pressure sensing and feedback with a minimalist design of the functional units. The proposed glove consists of modular strain and pressure sensors based on films of liquid metal microchannels and coin vibrators. Strain sensors located at the finger joints can simultaneously project the bending motion of the individual joint into the virtual space or robotic hand. For subsequent tactile interactions, the design of two symmetrically distributed pressure sensors and vibrators at the fingertips possesses capabilities for multi-directional pressure sensing and feedback by evaluating the relationship of the signal variations between two sensors and tuning the feedback intensities of two vibrators. Consequently, both dynamic and static multi-dimensional pressure communication can be realized, and the vibrational actuation can be monitored by a liquid-metal-based sensor via a triboelectric sensing mechanism. A demonstration of object interaction indicates that the proposed glove can effectively detect dynamic force in varied directions at the fingertip while offering the reconstruction of a similar perception via the haptic feedback function. This device introduces an approach that adopts a minimalist design to achieve a multi-functional system, and it can benefit commercial applications in a more cost-effective way.

A new distributed water pressure monitoring method for ground subsidence caused by groundwater overexploitation

Groundwater pressure is a key parameter in the analysis of ground subsidence laws and disaster-causing factors. However, existing sensors make it difficult to achieve distributed and accurate measurements of groundwater pressure. This paper presents a new distributed pressure sensor (DPS) based on optical frequency domain reflectometer (OFDR) for groundwater pressure accurate measurement. The comprehensive temperature influence coefficient was proposed to eliminate the influence of temperature. Tests were conducted to verify the performance of the DPS and analyze the influencing factors. Finally, the proposed method was applied to on-site monitoring of groundwater pressure in Ningbo, China. The test results show that a smaller helically wound pitch length of the fiber optic and a larger diameter piezoresistive element are conducive to improving the sensitivity of the sensor. The on-site monitoring results indicate that the DPS has obvious advantages over traditional pressure sensors and is an innovative means for groundwater pressure measurement.

The flexible and distributed pressure sensor with 64 units for on-line gait recognition analysis

With the rapid development of flexible electronic technology, human gait recognition device is also developing in the direction of flexibility, refinement, and intelligence. In this paper, a gait recognition system with the advantages of being non-invasive and flexible is proposed and prepared to collect complex pressure information of human plantar and identify different gaits accurately. A flexible and distributed pressure sensor with a structure of eight rows and eight columns is designed and fabricated by the screen printing process and micro-nano manufacturing technology. The insole shape can be placed directly into a sneaker for easy wearing, while 64 pressure sensing units allow for more accurate detection of complex plantar pressure information. In addition, based on the “voltage mirror” principle and the feature threshold analysis method, a distributed pressure acquisition circuit and an online gait recognition software are developed respectively to realize time-sharing decoupling of complex output signals from multiple pressure sensing units and online real-time display of different gaits. Finally, Different human gait recognition experiments have also been carried out. The results show that the test error of the pressure sensing unit is better than 8.28%. The gait recognition system can realize the reliable and accurate online real-time identification of slow walking, fast walking, and different leaning directions, which shows great potential and value in the fields of medical diagnosis, health monitoring, gait correction and artificial intelligence.

Analysis on the radial structure of rotating detonation wave in a hollow combustor

This experimental study discusses the radial structure of the rotating detonation wave (RDW) in a hollow chamber. The head chamber wall could be fabricated with quartz glass for high-speed visualizations or metal cover for high-frequency pressure measurement. The entire radial-stratified reaction zone was directly and continuously captured. The wall-attached bright zone indicated that the main reaction zone propagated along the chamber wall, but some deflagration was still observed in the inner zone. Based on the phase-averaged CH* chemiluminescence image, the radial thickness of the reaction zone was determined to be about 15–20 mm. The diminishing pressure peaks and deteriorating waveforms of the high-frequency pressure signals proved that the intensity of shock waves decreased along the chamber radius. The structure of RDW was reconstructed using radially distributed pressure sensors. Due to the compression effect of the concave chamber wall, a Mach reflection of detonation wave might occur. The detonation wave was connected to a diffracted shock, which stretched in the radial direction with decreasing intensity. The central angles calculated with the time-difference analysis demonstrated that the entire RDW bent forward in the inner zone of the chamber. Moreover, the radial thickness of the reaction zone and the curvature of shock waves increased with decreasing nozzle contraction ratio, which mainly attributed to the increasing expansion effect. This study demonstrated the distribution of reaction zone and the radial structures of shock waves for the RDW in a hollow combustor, contributing to the exploration of the flow and combustion process in a rotating detonation engine.

Pressure Feedback Control of Aerodynamic Loads on a Delta Wing in Transverse Gusts

A feedback active flow control (AFC) scheme is studied for control of unsteady aerodynamic loads that act on a generic tailless delta wing during transverse gust encounters. The transverse gust and the roll angle of the wing create an unsteady roll moment. The trailing edge actuators generate unbalanced lift increments on the two sides of the model to control the roll moment. Spatially distributed pressure sensors measure surface pressure on the suction side of the wing, and the real-time aerodynamic loads are estimated through models that are identified by the Sparse Identification of Nonlinear Dynamics algorithm. The aerodynamic load estimation is then used as a surrogate to provide the AFC system with a feedback signal to alleviate the unsteady roll moment due to the gust effect. A physical interpretation of the model identification results is made to locate the source of the lift and roll moment fluctuations in gust encounters. Experimental results show that the AFC effect with a momentum coefficient input of 2% is equivalent to 26° elevon deflection in terms of the roll moment change, and the AFC doubles the control authority relative to elevons. The real-time control results show that the pressure feedback control system reduces the mean roll moment error and suppresses the fluctuations to less than 20% of the uncontrolled fluctuation level at a high angle of attack.

Bioinspired dynamic soaring simulation system with distributed pressure sensors.

Inspired by the albatross, this paper presents the construction of a dynamic soaring simulation system with distributed pressure sensors. The advantage of our system lies in harvesting energy from the wind shear layer and estimating the wind information using a pressure-based sensor system. Specifically, the dynamic soaring simulation system contains an offline training stage and an online estimation and control stage. In the offline training stage, computational fluid dynamics simulations are conducted and used as the data source. A surrogate model is established to correlate the local flow conditions and the surface pressure at optimal sensor positions. In the online estimation and control stage, through sensing the pressure information, the real-time wind velocity and wind gradient are estimated by the surrogate model trained in the offline stage. Moreover, wind information is adopted in the simulation of dynamic soaring control. In this study, the simulation system was applied to linear and circular path-following tasks. It was found that the dynamic soaring simulation system with distributed pressure sensors provides an acceptable estimation of wind velocity and wind gradient with a certain time delay caused by numerical differentiation.

Flexible force-sensitive distributed pressure sensing system for soft connection of aircraft Cockpit Cover

With respect to the actual application of the edge bonding of transparent part of the fighter jet cockpit cover by soft connection, the flexible force-sensitive distributed pressure sensor system is developed, which covers the flexible force-sensitive sensor, calibration device, circuit and data analysis software. The pressure distribution during pressurizing of the edge bonding of multidimensional curved surface transparent parts is vividly showcased by 2D and 3D images. A number of people are assigned to carry out operation. Based on the pressure distribution map and data acquisition, it is determined that the existing bonding process has the serious decificiency of uneven pressure distributio that cannot be addressed, and there is huge potential for improvement.

High-sensitivity dynamic distributed pressure sensing with frequency-scanning φ-OTDR.

We propose a high-sensitivity dynamic distributed pressure sensor using frequency-scanning phase-sensitive optical time-domain reflectometry (φ-OTDR) in a single-mode fiber (SMF), where an injection locking laser working as both filter and amplifier is used to generate the multi-frequency signals under a double-sideband modulation. The pressure sensitivity of the SMF is measured to be 702.5 MHz/MPa, which is approximately 1000 times larger than that of the Brillouin optical time-domain analysis technique. Subsequently, a dynamic pressure experiment is carried out in the case of rapid pressure relief from 2 to 0 MPa so that a maximum sampling rate of 33.3 kHz for a 25-m SMF is achieved, and the measurement uncertainty of 0.61 kPa for the proposed scheme is demonstrated.

Dynamic Distributed Pressure Measurement Using Frequency-Agile Fast BOTDA

A distributed pressure sensor is proposed and designed for dynamic pressure measurement by using frequency-agile fast Brillouin optical time-domain analysis (BOTDA). A double coated single-mode fiber (SMF) is used as the sensing fiber because of its 1500- $\mu \text{m}$ thickness outer coating that can significantly improve the dependence of the Brillouin frequency shift on pressure. Then, the frequency-agile technique is used to generate frequency-agile pump pulse in BOTDA system so that a fast Brillouin gain spectrum distribution measurement can be achieved. An injection locked scheme is used as both optical filter and optical amplifier to improve the measurement accuracy. As a result, the static pressure sensitivity of the double coated fiber is −3.46 MHz/MPa with the pressure ranging from 0 to 30 MPa. Subsequently, a large dynamic range pressure measurement is performed with a sampling rate of 33.3 kHz and maximum sensing distance of 25 m. Furthermore, it is proved that the uncertainty of dynamic pressure measurement system is 0.03 MPa.

A point sound source location and detection method based on 19-element hemispheric distributed acoustic pressure sensor array

To solve the key problem of diagnosing the operating condition of an oil transfer pump unit in a 3D closed space, this paper presents an approach for a point sound source location and detection method based on a hemispheric distributed sound pressure sensor array. The array model consists of 19 sound pressure sensors acting in the radial direction and uniformly distributed over the hemispherical surface. A spatial rectangular coordinate system is established by taking the projection point of the central sensor arranged at the apex of the hemisphere to the ground as the origin of the spatial coordinates. With reference to the central sensor, the point sound source is located by selecting the maximum measured sound level and its spatial coordinate in each of the three layers of sensors surrounding it as parameters and using a triangular or a quadrilateral area location algorithm based on virtual instrument technology. According to the location of the source, the A-weighted sound level of the sound source point is derived by the inversion of the sound field distribution law. Results show that the triangular and quadrilateral area location algorithms are both effective. The errors in location become larger for a measured sound source far from the centre.

DMD-Based Background Flow Sensing for AUVs in Flow Pattern Changing Environments

This letter is concerned with real-time background flow field estimation using distributed pressure sensor measurements for autonomous underwater vehicles (AUVs). The goal of this study is to enhance environmental perception of AUVs especially in dynamic environments with changing flow patterns. Dynamic mode decomposition (DMD), a data-driven model reduction approach, is adopted to model the dynamic flow field using spatial basis modes and their corresponding temporal coefficients. This letter computes the DMD modes offline and applies a Bayesian filter to assimilate distributed pressure sensor measurements to estimate the DMD coefficients in real time. Further, fast Fourier transform (FFT) analysis is used to determine the flow pattern/model represented by DMD modes. Aiming to address the flow sensing problem in flow pattern changing environments, the proposed approach is expected to greatly improve environmental perception of AUVs in dynamic and complex flows. Both simulation and experimental results of flow sensing using three testing prototypes are presented to validate the proposed method.

Data-Driven Method for Flow Sensing of Aerodynamic Parameters Using Distributed Pressure Measurements

The real-time identification of inflow aerodynamic parameters such as the flow separation situation, angle of attack, and inflow velocity is challenging. In this paper, a new data-driven strategy is proposed to attain real-time identification of the inflow aerodynamic parameters through a combination of experimental data (offline) and distributed pressure sensor measurements (online). In the offline procedure, pressures on the airfoil surface are measured by 10 distributed sensors under 45 different conditions. Particle image velocimetry measurements are recorded to determine the correlation between the pressure distribution and the aerodynamic parameters. Proper orthogonal decomposition (POD) is applied on the pressure data under all conditions to encode this correlation into a three-dimensional domain, with a compression ratio of more than 90%. In the online procedure, the -nearest neighbor algorithm is used to identify the aerodynamic parameters of testing data in the established POD domain. Furthermore, a mathematical model is applied to optimize the pressure sensor locations. Using just four pressure measurement points, accuracy of 100% can be achieved for the flow separation detection, angle of attack, and inflow velocity. After flow separation, the new approach achieves an error of approximately for the angle of attack.

Plasma-Enhanced Chemical Vapor Deposition of Two-Dimensional Materials for Applications

ConspectusSince the rise of two-dimensional (2D) materials, synthetic methods including mechanical exfoliation, solution synthesis, and chemical vapor deposition (CVD) have been developed. Mechanical exfoliation prepares randomly shaped materials with small size. Solution synthesis introduces impurities that degrade the performances. CVD is the most successful one for low-cost scalable preparation. However, when it comes to practical applications, disadvantages such as high operating temperature (∼1000 °C), probable usage of metal catalysts, contamination, defects, and interstices introduced by postgrowth transfer are not negligible. These are the reasons why plasma-enhanced CVD (PECVD), a method that enables catalyst-free in situ preparation at low temperature, is imperatively desirable.In this Account, we summarize our recent progress on controllable preparation of 2D materials by PECVD and their applications. We found that there was a competition between etching and nucleation and deposition in PECVD, making it highly controllable to obtain desired materials. Under different equilibrium states of the competition, various 2D materials with diverse morphologies and properties were prepared including pristine or nitrogen-doped graphene crystals, graphene quantum dots, graphene nanowalls, hexagonal boron nitride (h-BN), B-C-N ternary materials (BCxN), etc. We also used mild plasma to modify or treat 2D materials (e.g., WSe2) for desired properties.PECVD has advantages such as low temperature, transfer-free process, and industrial compatibility, which enable facile, scalable, and low-cost preparation of 2D materials with clean surfaces and interfaces directly on noncatalytic substrates. These merits significantly benefit the as-prepared materials in the applications. Field-effect transistors with high motilities were directly fabricated on graphene and nitrogen-doped graphene. By use of h-BN as the dielectric interfacial layer, both mobilities and saturated power densities of the devices were improved owing to the clean, closely contacted interface and enhanced interfacial thermal dissipation. High-quality materials and interfaces also enabled promising applications of these materials in photodetectors, pressure sensors, biochemical sensors, electronic skins, Raman enhancement, etc. To demonstrate the commercial applications, several prototypical devices were studied such as distributed pressure sensor arrays, touching module on a robot hand for braille recognition, and smart gloves for recording sign language. Finally, we discuss opportunities and challenges of PECVD as a comprehensive preparation methodology of 2D materials for future applications beyond traditional CVD.

Distributed Pressure Sensing Using an Embedded-Core Capillary Fiber and Optical Frequency Domain Reflectometry

In this paper, we describe a distributed pressure sensor using a simplified and high sensitive microstructured optical fiber - the embedded-core fiber - and autocorrelation analysis of the data obtained from an optical frequency domain reflectometer (OFDR). The special fiber consists of a microcapillary, which has a germanium-doped core placed within the capillary wall. When this structure is subjected to pressure variations, an asymmetric stress distribution is induced within the fiber, entailing birefringence variations. Here, we show that the use of a commercial OFDR with submillimeter resolution-together with an autocorrelation data analysis routine in the spectral domain allows mapping the fiber birefringence and performing distributed pressure sensing. In the experiments, the fiber passed through two pressure chambers, which allowed for pressure to be locally and independently applied. No cross-sensitivity between the pressure points was observed. The embedded-core fiber exhibited a birefringence sensitivity to pressure of 3.8×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-7</sup> bar <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> , which is 21% higher than that measured in commercial photonic crystal fibers using the same setup.

Distributed optical fiber pressure sensors

Abstract The measurement of pressure by using distributed optical fiber sensors has represented a challenge for many years. While single-point optical fiber pressure sensors have reached a solid level of technology maturity, showing to be very good candidates in replacing conventional electrical sensors due to their numerous advantages, distributed sensors are still a matter of an intense research activity aimed at determining the most proper and robust pressure-sensitivity enhancement mechanism. This paper reviews early and recent works on distributed pressure sensors, classifying the sensors according to the sensing mechanism. For each type of mechanism, the issues and potentials are analyzed and discussed.

An Optical Fiber Distributed Pressure Sensing Cable With Pa-Sensitivity and Enhanced Spatial Resolution

In this paper, a high-sensitive, high-spatial resolution distributed pressure sensing cable employing standard single-mode fibers is presented and implemented. If measured with a distributed strain sensing interrogator with ${1}~\mu \varepsilon $ resolution, the pressure resolution and accuracy demonstrated with this prototype are approximately 5 Pa and 10 hPa, respectively, with an intrinsic maximum spatial resolution of 8.5 cm. In terms of Rayleigh spectral shift, the sensitivity is about −30 GHz/kPa. Above all, the interrogation of the cable does not require an interrogator with such high spatial resolution, and the design is compliant with any optical fiber distributed strain sensing technique, such as Brillouin- and Rayleigh-based ones.

Sensitivity-Enhanced Distributed Hydrostatic Pressure Sensor Based on BOTDA in Single-Mode Fiber With Double-Layer Polymer Coatings

A sensitivity-enhanced distributed hydrostatic pressure sensor based on Brillouin optical time domain analysis (BOTDA) technique is theoretically proposed and experimentally demonstrated, where double-layer polymer coatings are used on the single-mode fibers (SMF) to enhance the hydrostatic pressure sensitivity. The pressure-induced strain model of multilayer coated fibers based on Lame formula is established to analyze the enhancement mechanism of pressure sensitivity of Brillouin frequency shift (BFS). Simulation results show that BFS pressure sensitivity can be enhanced by increasing the outer coating radius or by decreasing the outer coating Young's modulus and Poisson's ratio. Four types of optical fibers are designed including single-coated and double-coated fibers to verify theoretical results, where the outer coating radius of double-coated fibers are 450, 1000, and 1500 μm, respectively. Experimental results show that the BFS pressure sensitivity are −0.75 MHz/MPa, −1.65 MHz/MPa, −2.66 MHz/MPa and −3.61 MHz/MPa in the range of 0–30 MPa after temperature compensation for above four kinds of fibers, respectively. The maximum pressure sensitivity is measured about five times higher than single-coated SMF, and the maximum measurement error of pressure sensing system is less than 0.09 MPa with a spatial resolution of 1.5 m.

Hydrothermally Grown ZnO Nanorods as Promising Materials for Low Cost Electronic Skin

AbstractZnO nanorods (NRs) are nanomaterials with a wide range of applications (photocatalysis, optoelectronics, catalysis, etc). One peculiar property of ZnO NRs is their piezoelectricity, which opens up a wealth of possibilities in the field of pressure sensors. In fact, thanks also to the recent availability of low cost hydrothermal growth, it is already possible to fabricate flexible, large area, self‐powered, distributed pressure sensors, with a high potential for use in robotics and prosthetics as “electronic skins”. This review focuses hence on ZnO NRs grown by the hydrothermal method, with an eye on the relationship between the reaction parameters and the resulting NRs morphology, and on their specific application in pressure sensing in terms of device design and performance.

Rotating Stall Induced Non-Synchronous Blade Vibration Analysis for an Unshrouded Industrial Centrifugal Compressor.

Rotating stall limits the operating range and stability of the centrifugal compressor and has a significant impact on the lifetime of the impeller blade. This paper investigates the relationship between stall pressure wave and its induced non-synchronous blade vibration, which will be meaningful for stall resonance avoidance at the early design phase. A rotating disc under a time-space varying load condition is first modeled to understand the physics behind stall-induced vibration. Then, experimental work is conducted to verify the model and reveal the mechanism of stall cells evolution process within flow passage and how blade vibrates when suffering such aerodynamic load. The casing mounted pressure sensors are used to capture the low-frequency pressure wave. Strain gauges and tip timing sensors are utilized to monitor the blade vibration. Based on circumferentially distributed pressure sensors and stall parameters identification method, a five stall cells mode is found in this compressor test rig and successfully correlates with the blade non-synchronous vibration. Furthermore, with the help of tip timing measurement, all blades vibration is also evaluated under different operating mass flow rate. Analysis results verify that the proposed model can show the blade forced vibration under stall flow condition. The overall approach presented in this paper is also important for stall vibration and resonance free design with effective experimental verification.

Distributed Pressure Sensing–Based Flight Control for Small Fixed-Wing Unmanned Aerial Systems

Small fixed-wing unmanned aerial systems (UAS) may require increased agility when operating in turbulent wind fields. In these conditions, conventional sensor suites could be augmented with additional flow-sensing to extend the aircraft’s usable flight envelope. Inspired by distributed sensor arrays in biological systems, a UAS with a chordwise array of pressure sensors was developed. Wind-tunnel testing characterized these sensors alongside a conventional airspeed sensor and an angle-of-attack (AoA) vane, and showed a single pressure measurement gave a linear response to AoA prestall. Flight tests initially manually piloted the vehicle through pitching maneuvers, then in a series of automated maneuvers based on closed-loop feedback using an estimate of AoA from the single pressure port. The AoA estimate was successfully used to control the attitude of the aircraft. An artificial neural network (ANN) was trained to estimate the AoA and airspeed using all pressure ports in the array, and validated using flight-trial data. The ANN more accurately estimated the AoA over a single-port method with good robustness to stall and unsteady flow. Distributed flow sensors could be used to supplement conventional flight control systems, providing enhanced information about wing flow conditions with application to systems with highly flexible or morphing wings.