High-precision Pressure Research Articles

Performance Study of F-P Pressure Sensor Based on Three-Wavelength Demodulation: High-Temperature, High-Pressure, and High-Dynamic Measurements.

F-P (Fabry-Perot) pressure sensors have a wide range of potential applications in high-temperature, high-pressure, and high-dynamic environments. However, existing demodulation methods commonly rely on spectrometers, which limits their application to high-frequency pressure signal acquisition. To solve this problem, this study developed a self-compensated, three-wavelength demodulation system composite with an F-P pressure sensor and a thermocouple to construct a comprehensive sensing system. The system produces accurate pressure measurements in high-temperature, high-pressure, and high-dynamic environments. In static testing at room temperature, the sensing system shows excellent linearity, and the pressure sensitivity is 158.48 nm/MPa. In high-temperature testing, the sensing system maintains high linearity in the range of 100 °C to 700 °C, with a maximum pressure-indication error of about 0.13 MPa (0~5 MPa). In dynamic testing, the sensor exhibits good response characteristics at 1000 Hz and 5000 Hz sinusoidal pressure frequencies, with a signal-to-noise ratio (SNR) greater than 37 dB and 45 dB, respectively. These results indicate that the sensing system proposed in this study has significant competitive advantages in the field of high-temperature, high-speed, and high-precision pressure measurements and provides an important experimental basis and theoretical support for technological progress in related fields.

Gas state equation and flow mechanism of gas–liquid two-phase flow in airlift pump system

Airlift pumps (ALPs) have a simple structure and significant application potential. However, previous studies on ALPs have generally assumed that the gas density remains constant. In this paper, the gas state equation (GSE) for ALP is established based on the van der Waals formula, which explicitly considers the density of gas. An electrical resistance tomography system is used to collect the gas void fractions at different heights under different gas flow rates, and an empirical formula for the gas void fraction is established. To verify the effectiveness of the proposed model, high-precision pressure sensors and a high-speed camera are used alongside an electrical resistance tomography system to determine the realistic ALP flow parameters. The results of 409 sets of experiments show that: (1) the gas in ALP cannot be regarded as ideal gas, because the ideal GSE cannot distinguish between different gas flow rates; (2) the state change of gas in ALP is a quasi-equilibrium process, whereby the GSE of ALP can be obtained from the pressures under several locations; (3) the axial pressures predicted by the proposed GSE for ALP are in good agreement with experimental data; and (4) a single parameter of the GSE uniquely determines the state process. The proposed model and the experimental data provide a new methodology and comprehensive references for studying the working mechanism and efficiency of ALPs.

A Continuous Non-Invasive Blood Pressure Prediction Method Based on Deep Sparse Residual U-Net Combined with Improved Squeeze and Excitation Skip Connections.

Arterial blood pressure (ABP) serves as a pivotal clinical metric in cardiovascular health assessments, with the precise forecasting of continuous blood pressure assuming a critical role in both preventing and treating cardiovascular diseases. This study proposes a novel continuous non-invasive blood pressure prediction model, DSRUnet, based on deep sparse residual U-net combined with improved SE skip connections, which aim to enhance the accuracy of using photoplethysmography (PPG) signals for continuous blood pressure prediction. The model first introduces a sparse residual connection approach for path contraction and expansion, facilitating richer information fusion and feature expansion to better capture subtle variations in the original PPG signals, thereby enhancing the network's representational capacity and predictive performance and mitigating potential degradation in the network performance. Furthermore, an enhanced SE-GRU module was embedded in the skip connections to model and weight global information using an attention mechanism, capturing the temporal features of the PPG pulse signals through GRU layers to improve the quality of the transferred feature information and reduce redundant feature learning. Finally, a deep supervision mechanism was incorporated into the decoder module to guide the lower-level network to learn effective feature representations, alleviating the problem of gradient vanishing and facilitating effective training of the network. The proposed DSRUnet model was trained and tested on the publicly available UCI-BP dataset, with the average absolute errors for predicting systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean blood pressure (MBP) being 3.36 ± 6.61 mmHg, 2.35 ± 4.54 mmHg, and 2.21 ± 4.36 mmHg, respectively, meeting the standards set by the Association for the Advancement of Medical Instrumentation (AAMI), and achieving Grade A according to the British Hypertension Society (BHS) Standard for SBP and DBP predictions. Through ablation experiments and comparisons with other state-of-the-art methods, the effectiveness of DSRUnet in blood pressure prediction tasks, particularly for SBP, which generally yields poor prediction results, was significantly higher. The experimental results demonstrate that the DSRUnet model can accurately utilize PPG signals for real-time continuous blood pressure prediction and obtain high-quality and high-precision blood pressure prediction waveforms. Due to its non-invasiveness, continuity, and clinical relevance, the model may have significant implications for clinical applications in hospitals and research on wearable devices in daily life.

Application of Remote Wireless Intelligent Layered Water Injection Technology in Dagang Oilfield

A remote wireless intelligent layered water injection technolo-gy is proposed to address the problems of traditional layered water in-jection well testing in oil fields, such as the inability to achieve continu-ous dynamic monitoring of injection parameters, high failure rate, and low success rate of testing and commissioning. The technology consists of a host computer client, a server, a surface controller, and an under-ground intelligent water distributor. The underground intelligent water distributor takes the injected water as the carrier, and uses the fluctua-tion of the water injection pressure in the tubing for signal transmission to realize two-way communication between the ground controller and the downhole intelligent water distributor. The underground intelligent water distributor integrates high-precision pressure gauges, controllable water nozzles, and calculation and control modules to form an intelli-gent control system, realizing the reception of ground down transmitted commands or data, the calculation and control of water injection flow rate of water nozzles, and the storage and upload of underground data. Remote wireless intelligent layered water injection technology has been applied in 43 wells, with a success rate of 100%. The maximum depth is 3897m, and the maximum wellbore inclination is 56.07°. This tech-nology realizes remote control of water injection wells, intelligent au-tomatic measurement and adjustment, real-time data monitoring, and automatic early warning functions, laying a foundation for the con-struction of “Digital Intelligence” oilfield.

Deep learning-driven super-resolution reconstruction of two-dimensional explosion pressure fields

Precise and rapid calculation of explosive loads on structures in specific explosion scenarios is crucial for blast-resistant design, emergency response and safety assessments of structures after disasters. However, available methods such as empirical models and numerical simulations are inadequate in meeting the fast computation demands for diverse explosion scenarios due to limitations in accuracy or computational cost. In order to obtain high-precision explosion pressure fields and overpressure time histories with low computational cost, this study presents a deep learning-based framework for reconstructing two-dimensional explosion pressure fields, which transforms low-resolution numerical simulation results into super-resolution outputs equivalent to high-resolution numerical simulation results. A super-resolution strategy, which concatenates high-resolution channels that record flow field information with the low-resolution channel, is proposed to improve the network performance. Based on the constructed dataset, a comparative study of three different networks is presented to assess their super-resolution applicability. Finally, the performance and generalization ability of the trained model is evaluated with super-resolution evaluation metrics, statistical evaluation metrics, and relative error distribution. The findings indicate that the super-resolution strategy can effectively improve the prediction accuracy of the network. The super-resolution model can not only provide high-credibility super-resolution pressure fields and pressure time histories, but also exhibits excellent generalization capabilities for explosive scenarios beyond the training dataset, therefore providing a new approach for realizing high-precision calculation of explosive flow fields and loads under diverse blast scenarios.

Cavitation evolution and flow field characteristics of transient flows with multi-point water-column separations in undulating pipeline

Transient flows with water-flow-induced multi-point cavitation inside an undulating pipeline are investigated experimentally under conditions of fast valve closure for three typical test cases by using high-precision pressure transducers, high-speed photography and particle image velocimetry (PIV) techniques. For low initial velocity condition, the transient pressure at the monitoring point (PT1) downstream the valve quickly decreases to the cavitation pressure and fluctuates near it. The leading-edge velocity of the dispersed bubble-like cavitation group first increases with its occurrence and then accelerates and reaches an extreme value before decreasing to zero due to the viscous force and the decrease of water flow inertia, and finally the water flows upstream in reverse, i.e. the leading-edge accelerates and collapses behind the valve. At the same time, the transient pressure rises sharply to maximum 81.86 m due to the return of the compression wave and then decreases sharply to cavitation again because of the switch of the pressure waves. Then, the second cavitation intensity is weak and the corresponding pattern is fog-like, and finally decreases gradually with a cyclic period of about 0.38 s. The transient pressure at the monitoring point (PT2) at the peak of the undulating pipeline also maintains at the cavitation pressure corresponding to the big bubble occurrence moment in addition to its fluctuation near the cavitation pressure including first and second cavitation. Its maximum pressure is 72.16 m and the corresponding cavitation pattern is small and bigger bubbles at different cavitation stages. For middle initial velocity, the typical pattern of the corresponding cavitation is the large cavity with free surface at PT2, the corresponding higher maximum pressures are 102.36 m at PT1 and 84.81 m at PT2. The evolution process of the cavity including bubble mergence, morphological deformation, motion and collapse is analysed based on the broken wave and hydraulic dynamic theories. For high initial velocity, larger cavities occur both downstream the valve and at the peak point of undulating pipeline, and thus the corresponding higher maximum pressures due to larger cavity collapse are 140.56 m at PT1 and 127.98 m at PT2. In particular, complete water column separation with transparent large cavity occur downstream the valve.

Data monitoring for indirect metering terminal of membrane gas measure device based on sensor network

In order to improve the data monitoring and information management capabilities of membrane gas measure device indirect metering terminals, a sensor network based data monitoring method for membrane gas measure device indirect metering terminals was proposed. The distributed and centralized sensor network node deployment method is used to achieve data collection for membrane gas measure device indirect metering terminals, and the collected membrane gas measure device indirect metering terminal data is segmented, fused, and reorganized. The distributed energy storage and constant volume two-level optimal control method is used to analyze the operation status of gas measure device indirect metering terminal data. The ZigBee networking protocol is used to build a network structure model for gas measure device indirect metering terminals, an integrated high-precision temperature and pressure sensor arranged parallel to the inner wall of the valve body is used to detect the temperature and pressure at the outlet of the membrane gas measure device. The temperature information is stored in DSP, and the user's expenses, system operation and maintenance, and peak shaving and valley filling benefits are taken as the parameters of the energy storage and constant volume outer layer model. The output stability of the indirect metering terminal data of the membrane gas measure device is analyzed in the high switching frequency mode. Combined with adaptive parameter adjustment, the indirect metering terminal control and data dynamic collection of the membrane gas measure device are realized. Realize dynamic monitoring of metering terminal data in wireless sensor network networking control mode. The test results show that using this method for indirect metering terminal data monitoring of gas measure devices has good output stability, strong dynamic fusion of sensing information, reduced metering errors, and improved metering accuracy of gas measure devices.

Effect of different injection fluids scenarios on swelling and migration of common clays in case of permeability variations: a micromodel study

Swelling and migration of present clays make damage to the oil reservoirs due to low salinity waterflooding (LSWF) can induce serious problems in the case of oil recovery improvement and researchers are trying to solve this problem. The purpose of this work is to investigate the mechanism of two phenomena of swelling and migration clays in the porous media of a reservoir rock by injecting a different composition of LSWF using a glass micromodel and providing the appropriate composition and pattern of injection with the removal of damage. Proper water flooding design, application of efficient swelling inhibitors, and migration control are among the most important methods to overcome the problem of formation damage due to swelling and migration of clays. A series of static (bulk or bottle test) and dynamic tests were carried out using a micromodel with a coating of kaolinite and montmorillonite clays in the vicinity and injection of different low salt water compositions. The type and amount of these clays were selected based on the results of XRD and SEM mineralogical tests on real reservoir rock, FW and diluted FW, SW and diluted SW, solution of 1% zirconium oxychloride in 20 times diluted seawater (SI), and composition of nanofluid MgO, SiO2, and Al2O3 in 20 times diluted. In the studies conducted by the micromodel, only the images taken were used in the analysis of the mechanisms, but here, the input and output pressures of the micromodel were recorded with high-precision pressure transmitters, and by using the differential pressure, the permeability was calculated and the formation damage index was introduced. The overlap of the interpretation of the captured images and the changes of the numerical parameter of the damage index in all stages of injection of smart water composition was considered to evaluate the simultaneous and separate mechanisms of swelling and migration of clays. The results of the experiments in this research show that clay swelling has destructive effects on permeability, and migration due to the transfer of clays from the porous medium can have promising effects on reducing the damage index in some conditions. And it is necessary to use the swelling control compound during the flooding process, but the migration inhibitor compound is not always suitable. Gradual reduction of salinity is also introduced as a pattern to prevent swelling damage or clay migration.In general, in this study, the best design and fluid engineering for smart water injection with the least damage in the micromodel scale was presented.

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.

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.

Pressure Drop Characteristics of the Reduced NGI Configuration with Several Common Glass Fiber Filters.

Background: Measurement of aerodynamic particle size distribution, a clinically relevant in vitro attribute of inhalable drug products, involves multistage cascade impactors and is tedious and expensive. A leading candidate for a quicker method is the reduced NGI™ (rNGI). This method involves placing glass fiber filters on top of the nozzles of a chosen NGI stage, selected often to collect all particles with an aerodynamic diameter smaller than approximately five microns. These filters contribute additional flow resistance that can alter the flow rate start-up curve, potentially affecting the size distribution and mass of the drug product dispensed by passive dry powder inhalers (DPIs). The magnitude of these additional flow resistance measurements is currently unreported in the literature. Materials and Methods: We placed glass fiber filters on top of the stage 3 nozzles of an NGI, along with the necessary support screen and hold-down ring. We measured the pressure drop across NGI stage 3 with the assistance of a delta P lid and a high-precision pressure transducer. With each filter material type and multiple individual filters, we gathered eight replicates at flow rates of 30, 45, and 60 L/min. Results: The filters typically doubled the total pressure drop through the NGI. For example, at a flow rate of 60 L/min, the Whatman 934-AH filters introduced a pressure drop of about 9800 Pa at stage 3, reducing the absolute pressure exiting the NGI to about 23 kPa below ambient, compared with a typical value of 10 kPa for the NGI alone at this flow rate. Conclusions: The pressure drop across typical filters is approximately equal to that through the NGI alone and therefore will affect the flow start-up rate intrinsic to compendial testing of passive DPIs. This change in start-up rate could cause differences between results of the rNGI configuration and those of the full NGI and will increase the required vacuum pump capacity.

The Effect of Pseudofrazil Particle Entrainment on Salinity Measurements

AbstractSalinity effects of particles entrained into conductivity cells have previously mainly been studied in the context of suspended sediment. Particles influencing conductivity cells can also be small ice crystals (frazil) that may form in supercooled water. The detection of supercooled water depends on accurate, high precision temperature, salinity and pressure measurements. As it is currently not possible to measure salinity in situ, the standard procedure is to measure conductance over a known volume and calculate salinity. Frazil ice entrained into a conductivity cell changes the volume of conductive fluid in the conductivity cell, thus changing the conductivity, salinity and supercooling measurements. We present results on the effect of entraining microplastic into a Sea‐Bird Electronics conductivity cell to simulate the effect of frazil. We show that particle volumes comparable to frazil volumes observed in the ocean change the measured conductivity and led to changes in calculated supercooling between 0.3 and 10 mK, possibly up to the same order of magnitude as naturally observed supercooling in the ocean. Further, we demonstrate that where supercooling is present, natural frazil ice concentrations can have an appreciable effect on parameters calculated with both the Equation of State of Seawater 1980 and Thermodynamic Equation of Seawater 2010 equations of state of seawater. Thus, to ensure accurate measurements in locations of very high frazil concentration, the entrainment of frazil needs to be prevented, which is not possible with methods currently available, or corrected for. An example for such a correction is given and could be modified to be applicable to other particles, for example, sediment.

Research on Pressure Control of an Electro-Hydraulic Servo System Based on Sliding-Mode Variable-Structure Direct Torque Control

Taking a direct-drive volume control (DDVC) electro-hydraulic servo system as the research object and aiming at the problems of the servo motor torque fluctuation, high-precision system pressure control, and dynamic response of the system, based on traditional motor direct torque control (DTC), a motor direct torque control method based on a sliding-mode variable structure is proposed to control the system pressure. The motor torque loop is part of the inner control loop and has a rapid dynamic response speed, resulting in higher pressure control accuracy. A nonlinear mathematical model was established for the DDVC electro-hydraulic servo system. The switch meter hysteresis controller in the traditional DTC system was replaced with space vector pulse-width modulation technology. Then, the PID control module in space vector modulation technology was replaced with high-order sliding-mode variable-structure control. Through the coupling relationship between the electric machine and the constant-displacement pump, the pressure can be controlled with high precision using motor torque control. Finally, using the MATLAB/Simulink simulation platform and the DDVC electro-hydraulic servo system simulation model, the proposed theoretical approach to torque control was verified on the basis of simulations and experiments, and the performance with regard to pressure control in the hydraulic system was observed. The simulation and experimental results show that the designed torque control is able to effectively reduce the motor torque fluctuation and improve the dynamic response characteristics of the system. The system pressure control is superior to traditional pressure control methods based on speed regulation, and it has higher control accuracy and a better dynamic response.

Analysis and performance assessment of the use of ammonia-based nano additive for lean combustion

In recent years, considerable progress has been made in exploring new applications of fuel additives to reduce emissions. Reduction of total nitrogen oxide (NOx) emissions can be achieved by decreasing the flame temperature by using fuel emulsified with water and/or using ammonia-based nano additives such as urea. The use of water as part of the hydrocarbon fuel is also one of the prospective directions in the development of new types of fuel systems. For the preparation of emulsified fuel, it is desirable to achieve greater stability of the emulsified fuel with minimum expenditure of chemicals and energy, so that the emulsified fuel can be used for a longer period. The paper analyzed the influence of nano-dispersed urea particles, water, and surfactant (Span 80/Tween 80) on the combustion stability and emission characteristics of aviation fuel. The experimental campaign was conducted on a test stand (a 300kW liquid vortex combustor of 300 kW) consisting of a cylindrical combustion chamber with four optical windows and equipped with high-precision pressure sensors, thermocouples, and an exhaust gas analyzer for acquiring emissions. The experimental campaign was conducted at a constant fuel/air ratio (Φ). One of the main focus is related to the stability of the emulsion. Chemiluminescence imaging was performed to characterize the effects of the additive on flame emissions. In addition, a statistical and spectral analysis was performed using the pressure sensor for instability analysis. Exhaust gas analysis was performed both with the additive described above and without additive for a constant Φ condition. The analysis was performed for NOx, carbon monoxide (CO) and carbon dioxide (CO2) and oxygen (O2).

Dual Fabry-Perot interferometers gas pressure sensor in a parallel configuration based on a hollow core Bragg fiber and the harmonic Vernier effect.

An ultra-high sensitivity parallel-connected Fabry-Perot interferometers (FPIs) pressure sensor is proposed and demonstrated based on hollow core Bragg fiber (HCBF) and harmonic Vernier effect. The HCBF functions as a micro Fabry-Perot cavity and possesses low transmission loss. One FPI acts as the sensing unit while the other FPI is used as the reference unit to generate the Vernier effect. The sensing FPI was prepared by fusion splicing a section of HCBF between a single-mode fiber (SMF) and a hollow silica tube (HST), and the reference FPI was fabricated by sandwiching a piece of HCBF between two SMFs. Two FPIs with very different free spectral ranges (FSRs) in the fringe pattern were connected to the 2 × 2 coupler parallelly, which realizes the harmonic Vernier effect and ensures the stability of the interference fringe. Laboratory results exhibited that the pressure sensitivity can be enhanced to 119.3 nm/MPa within 0-0.5 MPa by the proposed sensor. Moreover, low-temperature crosstalk of 0.074 kPa/° was achieved. Compared with the traditional optical fiber gas pressure sensor, the advanced sensor features high sensitivity, stability, easy fabrication, and fast response, which can be a promising candidate for real-time and high-precision gas pressure monitoring.

Double-layered laser induced graphene (LIG) porous composites with interlocked wave-shaped array for large linearity range and highly pressure-resolution sensor

There is an urgent need for developing flexible pressure sensors with ultra-high pressure-resolution and wide linear range to expand the application of wearable electronic devices. Here, a strategy was proposed for fabricating a LIG composite with wave-shaped array and multi-scale porous structure for wide-range and high-precision pressure detection. The synergism of the internal three-dimension porous structure and the inter-layer interlocked wave-shaped array endows the assembled double-layer LIG composite with numerous variable electrical conductive paths and easy deformation. Therefore, great improvements have been achieved in detection broad range and accuracy, exhibiting a large linearity range (0–100 kPa) and high pressure-resolution (millipascal-scale) over the full linearity range. These sensing properties make the double-layer LIG composites feasible for detecting subtle physiological signals and monitoring large human motions. Meanwhile, integrating the synthesis of graphene as active material and the design of flexible sensing structure by laser direct writing (LDW) technique provides an effective strategy for manufacturing high performance sensors with simple and low cost.

Pressure sensitivity for head, face and neck in relation to soft tissue

Pressure sensitivity research on the head, face, and neck is critical to develop ways to reduce discomfort caused by pressure in head-related products. The aim of this paper is to provide information for designers to be able to reduce the pressure discomfort by studying the relation between pressure sensitivity and soft tissue in the head, face and neck. We collected pressure discomfort threshold (PDT) and pressure pain threshold (PPT) from 119 landmarks (unilateral) for 36 Chinese subjects. Moreover, soft tissue thickness data on the head, face and neck regions of 50 Chinese people was obtained through CT scanning while tissue deformation data under the PDT and PPT states was obtained from literature. The results of the three-elements correlation analysis revealed that soft tissue thickness is positively correlated with deformation but not an important factor in pressure sensitivity. Our high-precision pressure sensitivity maps confirm earlier findings of more rough pressure sensitivity studies, while also revealing additional fine scale sensitivity differences. Finally, based on the findings, a high-precision "recommended map” of the optimal stress-bearing area of the head, face and neck was generated.

High-precision whispering gallery microsensors with ergodic spectra empowered by machine learning

Whispering gallery mode (WGM) microcavities provide increasing opportunities for precision measurement due to their ultrahigh sensitivity, compact size, and fast response. However, the conventional WGM sensors rely on monitoring the changes of a single mode, and the abundant sensing information in WGM transmission spectra has not been fully utilized. Here, empowered by machine learning (ML), we propose and demonstrate an ergodic spectra sensing method in an optofluidic microcavity for high-precision pressure measurement. The developed ML method realizes the analysis of the full features of optical spectra. The prediction accuracy of 99.97% is obtained with the average error as low as 0.32 kPa in the pressure range of 100 kPa via the training and testing stages. We further achieve the real-time readout of arbitrary unknown pressure within the range of measurement, and a prediction accuracy of 99.51% is obtained. Moreover, we demonstrate that the ergodic spectra sensing accuracy is∼11.5%higher than that of simply extracting resonating modes’ wavelength. With the high sensitivity and prediction accuracy, this work opens up a new avenue for integrated intelligent optical sensing.

Blood pressure monitoring techniques in the natural state of multi-scenes: A review.

Blood pressure is one of the basic physiological parameters of human physiology. Frequent and repeated measurement of blood pressure along with recording of environmental or other physiological parameters when measuring blood pressure may reveal important cardiovascular risk factors that can predict occurrence of cardiovascular events. Currently, wearable non-invasive blood pressure measurement technology has attracted much research attention. Several different technical routes have been proposed to solve the challenge between portability or continuity of measurement methods and medical level accuracy of measurement results. The accuracy of blood pressure measurement technology based on auscultation and oscillography has been clinically verified, while majority of other technical routes are being explored at laboratory or multi-center clinical demonstration stage. Normally, Blood pressure measurement based on oscillographic method outside the hospital can only be measured at intervals. There is a need to develop techniques for frequent and high-precision blood pressure measurement under natural conditions outside the hospital. In this paper, we discussed the current status of blood pressure measurement technology and development trends of blood pressure measurement technology in different scenarios. We focuses on the key technical challenges and the latest advances in the study of miniaturization devices based on oscillographic method at wrist and PTT related method at finger positions as well as technology processes. This study is of great significance to the application of high frequency blood pressure measurement technology.

A Research of High-Precision Pressure Regulation Algorithm Based on ON/OFF Valves for Aircraft Braking System

The aircraft braking system is a critical system used to slow down and stop the aircraft. Typically, the aircraft braking system usually uses the electro-hydraulic pressure servo-valve (EHPSV) to regulate the braking pressure of the aircraft. However, the pilot stage of EHPSV which has very precise orifice is easy to be blocked and leads to terrible fault. The <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> / <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> valve is robust to oil contamination and has better stability, but it is challenging to achieve high-precision pressure regulation. In order to guarantee the braking efficiency of aircraft, a high-precision pressure regulation algorithm is required. In this study, a algorithm with <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> / <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> valve array unit is studied to optimize the pressure regulation performance. The characteristics of the <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> / <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> valve under different actuation times and pressures are derived. Based on this characteristics, a novel algorithm which can predict the required number of <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> / <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> valves and actuation time obtained by the unknown input state observer. Then the proposed algorithm is validated both by simulations and experiments. The results show that the proposed regulation algorithm in this study can achieve high-precision pressure regulation for aircraft braking application, which the regulation precision is better than 0.2 MPa, and the overshoot is less than 2.5%.