Flow Sensor Research Articles

Two deep learning methods in comparison to characterize droplet sizes in emulsification flow processes

AbstractFor reliable supervision in multiphase processes, the droplet size represents a critical quality attribute and needs to be monitored. A promising approach is the use of smart image flow sensors since optical measurement is the most commonly used technique for droplet size distribution determination. For this, two different AI-based object detection methods, Mask RCNN and YOLOv4, are compared regarding their accuracy and their applicability to an emulsification flow process. Iterative optimization steps, including data diversification and adaption of training parameters, enable the models to achieve robust detection performance across varying image qualities and compositions. YOLOv4 shows better detection performances and more accurate results which leads to a wider application window than Mask RCNN in determining droplet sizes in emulsification processes. The final droplet detection model YOLOv4 with Hough Circle (HC) for feature extraction determines reliable droplet sizes across diverse datasets of liquid-liquid flow systems (disperse phase content 1–15 vol.-%, droplet size range 5–150 μm). Evaluating the adjustment of Confidence Scores (CS) ensures statistical representation of even smaller droplets. The droplet detection performance of the final YOLOv4 model is compared with a manual image processing method to validate the model in general as well as its accuracy and reliability. Since YOLOv4 in combination with Hough Circle (HC) shows an accurate and robust detection and size determination, it is applicable for online monitoring and characterization of various liquid-liquid flow processes. Graphical abstract

Assessment of sensor-based automatic smart watering unit for paddy nurseries under Indian perspective

A sensor-based automatic watering unit was developed to irrigate the paddy seedling trays. The watering unit comprised six flat spray nozzles with a direct current (DC) water pump and flow sensor, and these were kept at the top of the conveyor frame, which was actuated by a DC water pump with a solenoid valve to drop the water in trays. The actuation of the DC solenoid valve was controlled by a limit switch fitted to the conveyor frame, which sensed the moving trays on the conveyor. The performance of the developed unit was evaluated, and process optimization was performed using the Inscribed Central Composite Design in Response Surface Methodology. The effect of main operating parameters- chain conveyor speed (0.123, 0.196, and 0.27 m/s), spray operating pressure (1.5, 3.0, and 4.5 kg/cm2), and spray height (10,30 and 50 cm) on the performance of the sensor-based automatic watering unit was studied in terms of the amount of water spray requirement and coefficient of water spray uniformity in trays. The responses of the unit at its optimal parameter operation (spray operating pressure 4.5 kg/cm2, spray height 10 cm, and chain conveyor speed 0.14 m/s) were found to be 1.31 L/tray as the amount of water spray requirement and 92.41 % as the coefficient of water spray uniformity of the unit. Hence, it can be an efficient substitute with significantly less power consumption 41 W with a higher working capacity of 780 trays/h for watering into the paddy tray nursery. The developed sensor-based automatic smart watering unit saves irrigation water per square area of 68.90 %, 76.13 %, and 82.31 % compared to existing drip, sprinkler, and flood irrigation methods in mat-type paddy nurseries. The developed sensor-based automatic smart watering unit saves the watering cost INR 11,567.16 (140.02 USD) per hectare, reducing cost by 63.7 % compared to manual watering in the mat-type nursery preparation. Thus, an automatic smart watering unit in a paddy tray nursery offers consistent and uniform watering from an Indian perspective, promoting uniform germination, crop growth, and establishment. It conserves water by ensuring the right amount of water is applied at the right time, avoiding overwatering or under-watering.

Smart Industrial Internet of Things Framework for Composites Manufacturing.

Composite materials are increasingly important in making high-performance products. However, contemporary composites manufacturing processes still encounter significant challenges that range from inherent material stochasticity to manufacturing process variabilities. This paper proposes a novel smart Industrial Internet of Things framework, which is also referred to as an Artificial Intelligence of Things (AIoT) framework for composites manufacturing. This framework improves production performance through real-time process monitoring and AI-based forecasting. It comprises three main components: (i) an array of temperature, heat flux, dielectric, and flow sensors for data acquisition from production machines and products being made, (ii) an IoT-based platform for instantaneous sensor data integration and visualisation, and (iii) an AI-based model for production process forecasting. Via these components, the framework performs real-time production process monitoring, visualisation, and prediction of future process states. This paper also presents a proof-of-concept implementation of the framework and a real-world composites manufacturing case study that showcases its benefits.

Fabrication and characterization of high-sensitivity, wide-range, and flexible MEMS thermal flow velocity sensors

With the rapid development of various fields, including aerospace, industrial measurement and control, and medical monitoring, the need to quantify flow velocity measurements is increasing. It is difficult for traditional flow velocity sensors to fulfill accuracy requirements for velocity measurements due to their small ranges, susceptibility to environmental impacts, and instability. Herein, to optimize sensor performance, a flexible microelectromechanical system (MEMS) thermal flow sensor is proposed that combines the working principles of thermal loss and thermal temperature difference and utilizes a flexible cavity substrate made of a low-thermal-conductivity polyimide/SiO2 (PI/SiO2) composite porous film to broaden the measurement range and improve the sensitivity. The measurement results show that the maximum measurable flow velocity can reach 30 m/s with a resolution of 5.4 mm/s. The average sensitivities of the sensor are 59.49 mV/(m s−1) in the medium-to-low wind velocity range of 0–2 m/s and 467.31 mV/(m s−1) in the wind velocity range of 2–30 m/s. The sensor proposed in this work can enable new applications of flexible flow sensors and wearable devices.

A novel evaluation method of the aging performance of MEMS flow sensor

The development of Micro Electro Mechanical Systems (MEMS) flow sensor towards high level market applications generates various challenges, in particular also on the reliable functionality. With the advancement of reliability engineering technology, aging phenomenon of MEMS devices has been widely concerned. As a result, an aging evaluation method is essential. The accelerated aging testing (AAT) is the most widely used in traditional aging methods. However, its performance is limited by highly economic and time cost. In this paper, a novel aging effect model is proposed, in which a comprehensive approach that integrates AAT, lifetime distribution modeling, and either Finite Element Modeling Simulation (FEMS) or fatigue simulation (FS) as fundamental is explored. However, the difference from the conventional approach was that the AAT results is imported in FS, to confirm fatigue analysis, while FS predictions are instrumental in analyzing degradation or fatigue phenomena and estimation lifetime. In this way, aging performance is illustrated detailed with the lower aging cost and high efficiency. Meanwhile, the results of proposed FS are verified by a thermal cycle (TC) AAT. Specifically, the resistor degradation mechanism, the characteristic parameter degradation is calculated. Moreover, the lifetime evaluation was acquired by the Arrhenius model. Finally, the proposed aging performance evaluation method can be applied to both discrete devices and modules. Compared with the traditional aging method the high aging cost can be eliminated, and the proposed aging evaluation strategy can be used in various temperature conditions.

Detecting Intrathoracic Airway Closure during Prehospital Cardiopulmonary Resuscitation Using Quasi-Static Pressure-Volume Curves: A Pilot Study.

Background: Intrathoracic airway closure frequently occurs during cardiac arrest, possibly impairing ventilation. Previously, capnogram analysis was used to detect this pathophysiological process. In other populations, quasi-static pressure-volume curves obtained during constant low-flow inflations are routinely used to detect intrathoracic airway closure. This study reports the first use of quasi-static pressure-volume curves to detect intrathoracic airway closure during prehospital cardiopulmonary resuscitation. Methods: Connecting a pressure and flow sensor to the endotracheal tube enabled the performance of low-flow inflations during cardiopulmonary resuscitation using a manual resuscitator. Users connected the device following intubation and performed a low-flow inflation during the next rhythm analysis when chest compressions were interrupted. Determining the lower inflection point on the resulting pressure-volume curves allowed for the detection and quantification of intrathoracic airway closure. Results: The research device was used during the prehospital treatment of ten cardiac arrest patients. A lower inflection point indicating intrathoracic airway closure was detected in all patients. During cardiac arrest, the median pressure at which the lower inflection point occurred was 5.56 cmH20 (IQR 4.80, 8.23 cmH20). This value varied considerably between cases and was lower in patients who achieved return of spontaneous circulation. Conclusions: In this pilot study, quasi-static pressure-volume curves were obtained during prehospital cardiopulmonary resuscitation. Intrathoracic airway closure was detected in all patients. Further research is needed to determine whether the use of ventilation strategies to counter intrathoracic airway closure could lead to improved outcomes and if the degree of airway closure could serve as a prognostic factor.

A sensorless centrifugal pump operation states estimation method based on HSSA-BPNN

As a liquid transportation equipment, centrifugal pumps find extensive use in industrial process control. Certain environments involving high temperature, high pressure, and highly corrosive media may not permit the installation of flow and pressure sensors. Consequently, accurately estimating the operating status of centrifugal pumps in the absence of sensors has become a prominent research focus. However, the precision of existing sensorless estimation methods remains a concern. This study introduces a HSSA-BPNN model utilizing valve opening degree, motor rotational speed and shaft power as input variables. A hybrid strategy improved sparrow search algorithm (HSSA) is developed to optimize the back propagation neural network (BPNN). Experimental results demonstrate a low mean absolute percentage error (MAPE) of the test data, which are 2.2741% and 1.6502%, respectively. The absolute errors of flow rate and head are below 0.3 m3/h and 0.5 m, respectively, with relative errors less than 4% and 3%, meeting practical applications.

Microfluidic flow sensor based on chronoamperometric measurements in a microchannel

Microfluidics explores the fluid behavior at micron scale and is therefore suited to applications that need precise manipulation of fluids at small length or volume scales. In a span of over two decades, microfluidics has become an essential tool for modern genome sequencing platforms, single-cell analysis and common diagnostic tests. Despite many successful applications, the field has various challenges: Fabrication processes are yet to transition to commercial materials, microfluidic systems are reliant on skilled operators, and supporting equipment. Technological innovations in automation are needed to enable easy to use, completely on-chip microfluidic systems. Sensors are a critical component of any automated system. Fluid and flow properties such as flow rate, pressure, temperature, viscosity are critical to applications in drug development, and material/chemical synthesis. The flow rate (μL/min or nL/min) predictions based on external (off-chip) flow measurements can lead to erroneous calculations. The present work explores a technique based on chronoamperometry to measure flow rates inside a microchannel. Chronoamperometry based redox cycling of aqueous NaCl was performed by using interdigitated electrodes (IDE). The sensor measures current transients (which are modulated by the flow rate of the solution) effected by redox reactions on surface of the electrodes. The sensor demonstrated a sensitivity of 0.016 (μL/min)−1 change in charge transfer per unit change in flow rate and 3σ resolution of 9.3 μL/min. The calibration curve is linear in the range 0 – 200 μL/min, with a limit of detection (LoD) of 5 μL/min, making it suitable for various microfluidics applications.

Initial Study of the Onsite Measurement of Flow Sensors on Turbine Blades (SOTB).

This paper presents a new framework using MEMS flow sensors on turbine blades (SOTB) to investigate unsteady flow features of a rotating wind turbine. Self-heating flow sensors were implemented by the U18 complementary metal-oxide semiconductor (CMOS) MEMS foundry provided by Taiwan Semiconductor Research Institute (TSRI). Flow sensor chips with a size of 1.5 mm × 1.5 mm were parylene-coated, output via a wireless data acquisition system (WDAQ), and mounted at the root, middle and tip of a 1.2 m diameter semi-rigid turbine blade of a 400 W horizontal axis wind turbine (HAWT). The instantaneous angles of attack (AOAs) of the SOTB were found to be 46~62°, much higher than the general stall AOA of 15°, but were accurate considering the normal detection of the flow sensors. The computational fluid dynamics (CFD) simulation of the HAWT was also compared with the SOTB output. The onsite measurement herein revealed that the 3D secondary flow increment, mostly obvious near the middle part of the turbine blades, degraded both the sensor and the turbine performance and initially justified the onsite measurement application.

THE MEASUREMENT QUALITY EVALUATION OF AN ULTRASONIC FLOW SENSOR WITH A COMPLEX MEASURING PATH TRAJECTORY

Over the past ten years, ultrasonic measuring instruments have become most widespread in industrial measurements of the flow and quantity of various energy resources. Such instruments differ in design, method of obtaining the output signal, number and topology of acoustic waves propagation and, accordingly, have different metrological performances. The accuracy of the measured signal formation is determined by the quality of the flow sensor. At the same time, the components of quality are metrological performances, manufacturability of the design, ease of setup, cost and others. The purpose of the work is to compare, analyze and evaluate the quality of flow measurements when using a single-channel ultrasonic sensor with a complex trajectory of the measuring beam and a multi-path (multichord) ultrasonic sensor. As a result of simulation modeling, distributions of flow velocities in longitudinal sections and cross sections were obtained, correction factors for the measured signal were determined, and pressure losses were calculated. A comparative analysis of the measurement quality of the investigated flow sensors made it possible to identify the advantages of using a single-path flow transducer with acoustic wave reflection. We are talking about the possibility of accurately outputting a useful signal, higher metrological sensitivity, higher measurement accuracy, as well as minimal impact on the measured medium due to the creation of smaller geometrically sized local hydrodynamic resistance along the length of the measuring path. The further research prospect is the study of ultrasonic flow measuring sensors with different topologies of acoustic channels when measuring and recording flow and quantity for different flow regimes of the measured medium.

Design and Performance Analysis of a Torque-Based Optical Fiber Flow Sensor

Design and Performance Analysis of a Torque-Based Optical Fiber Flow Sensor

Micromachined needle-like calorimetric flow sensor for sap flux density measurement in the xylem of plants

Miniaturized silicon thermal probes for plant’s sap flow measurement, or micro sap flow sensors, have advantages in minimum invasiveness, low power consumption, and fast responses. Practical applications in sap flow measurement has been demonstrated with the single-probe silicon micro sensors. However, the sensors could not detect flow directions and require estimating zero sap flow output that leads to significant source of uncertainty. Furthermore, silicon-needles would break easily during the insertion into plants. We present the first three-element micro thermal sap flow sensor packaged on a durable printed circuit board needle that can measure bidirectional flows with improved dynamics and precision. The performance of the newly designed calorimetric flow sensor was confirmed through precision calibration and field test on tomato stems. A calibration curve for a tomato stem was obtained with a sensitivity of 0.299 K/(µL mm−2 s−1) under the maximum temperature increase of 4.61 K. Results from the field test for one month revealed a correlation between the measured sap flux density and related conditions such as solar radiation, vapor pressure deficit, sunshade and irrigation. The developed sensor will contribute to practical long-term sap flow monitoring for small and delicate plants with minimal physical invasion.

Post Study Design of Wireless Network for the Water Dilemma in the city of Rujban

Providing water for daily life usage is one of the biggest obstacles facing the growth and development of cities not only in Libya but in many countries of the world. The city of Rujban faces this crisis despite the passage of more than five decades in trying to resolve this issue. We did some deep research and study on the water system operation problem which we divided into three parts: Karthoom Automated Control System (KACS), Idref Automated Control System 1(IACS1), Idref Automated Control System 2 (IACS2) because water is pumped on 3 different stages. The IACS1 consists of two main parts: transmitter/collector tank on one side and receiver / pumps on the other side. The transmitter end consists of a microcontroller, three stage level sensor, two water flow sensors and an RF transmitter. The other end consists of two water pumping pump and an RF receiver. The system will be automated by the use of a microcontroller in which each level of the collector tank will be designed to turn on just one or both pumps of in the case there is certain amount of water, which can be determined by water level sensor, in Karthom collection tank. A crucial part of this coordination is the flow meter which will indicate if the pump is operational or not and detect whether or not there is water leakage, all of which will be demonstrated on an LCD screen. In this paper, we will design a wireless communication network for IACS1.

Engineering microvascular networks using a KLF2 reporter to probe flow-dependent endothelial cell function

Shear stress generated by the flow of blood in the vasculature is a potent regulator of endothelial cell function and vascular structure. While vascular responses to flow are complex and context-dependent, endothelial cell signaling in response to shear stress induced by laminar flows is coordinated by the transcription factor KLF2. The flow-dependent expression of KLF2 in endothelial cells is associated with a quiescent, anti-inflammatory phenotype and has been well characterized in two-dimensional systems but has not been studied in three-dimensional in vitro systems. Here we develop engineered microvascular networks (MVNs) that incorporate a KLF2-based endothelial cell flow sensor within a microfluidic chip, apply continuous flow using an attached microfluidic pump, and study the effects of this flow on vascular structure and function. We found that application of flow to MVNs for 48 h resulted in increased expression of the KLF2 reporter, larger vessel diameters, and decreased vascular branching and resistance. Notably, vessel diameters after the application of flow were independent of initial MVN morphologies. Finally, we found that MVNs exposed to flow have improved vascular barrier function and decreased platelet adhesion. MVNs with KLF2-based flow sensors represent a novel, powerful tool for evaluating the structural and functional effects of flow on engineered three-dimensional vascular systems.

A New Plant-Wearable Sap Flow Sensor Reveals the Dynamic Water Distribution during Watermelon Fruit Development

This study utilized a plant-wearable sap flow sensor developed by a multidisciplinary team at Zhejiang University to monitor water distribution patterns in watermelon fruit stalks throughout their developmental stages. The dynamic rules of sap flow at different stages of fruit development were discovered: (1) In the first stage, sap flow into the fruit gradually halts after sunrise due to increased leaf transpiration, followed by a rapid increase post-noon until the next morning, correlating with fruit expansion. (2) In the second stage, the time of inflow sap from noon to night is significantly shortened, while the outflow sap from fruit is observed with the enhancement of leaf transpiration after sunrise, which is consistent with the slow fruit growth at this stage. (3) In the third stage, the sap flow maintains the diurnal pattern. However, the sap flow that inputs the fruit at night is basically equal to the sap flow that outputs the fruit during the day; the fruit phenotype does not change anymore. In addition, a strong correlation between the daily mass growth in fruit and the daily sap flow amount in fruit stalk was identified, validating the sensor’s utility for fruit growth monitoring and yield prediction.

Comparison between Direct and Indirect Heat Flux Measurement Techniques: Preliminary Laboratory Tests

Direct and indirect approaches can be employed for estimating the heat flow through components in different application fields. In the building sector, the thermometric method is often applied by professionals for thermal transmittance evaluations. However, miscalculations can derive from inaccurate total heat transfer coefficients, and a consensus regarding the appropriate value to employ remains to be determined. Here, an apparatus was realized for laboratory tests and heat flux measurements were performed following direct and indirect approaches. Data acquired through a common heat flow sensor were compared with those computed through a post-processing based on radiative and convective estimations. The results were affected by the specific correlation adopted for computing the convective coefficients, with the percentage differences ranging from −9.8% to −0.4%. New measurement systems could be designed for automatically computing heat fluxes through indirect approaches, thus providing alternative solutions in the panorama of non-destructive tests for building energy diagnosis.

Exploring a reversible adaptation of conventional HPLC for capillary-scale operation

This study introduces a feasible approach for utilizing a conventional High-Performance Liquid Chromatography (HPLC) instrument at the capillary scale (1 - 10 µL/min). The development of an active flow splitter and an adapted UV-visible (UV–vis) detection cell are described. The system employs an Arduino Uno board to monitor a flow sensor and control a stepper motor that automates a split valve to achieve capillary-scale flow rates from a conventional pump. A capillary UV–vis cell compatible with conventional detectors, featuring an optical path length with a volume of 14 nL, was developed to address the detection challenges at this scale and minimize extra column band broadening. The system performance was assessed by a lab-packed LC capillary column with 0.25 mm x 15 cm dimensions packed with 3.0 µm C18 particles. Model compounds, particularly polycyclic aromatic hydrocarbons (PAHs), were employed to assess the functionality of all developed components in terms of theoretical plates, resolution, and band broadening. The proposed system is a profitable, reliable, and cost-effective tool for miniaturized liquid chromatography.

Evaluating Airflow Sensor Methods: Precision in IndirectCalorimetry.

This study assesses the impact of three volumetric gas flow measurement methods-turbine (fT); pneumotachograph (fP), and Venturi (fV)-on predictive accuracy and precision of expired gas analysis indirect calorimetry (EGAIC) across varying exercise intensities. Six males (Age: 38 ± 8 year; Height: 178.8 ± 4.2 cm; : 42 ± 2.8 mL O2 kg-1 min-1) and 14 females (Age = 44.6 ± 9.6 year; Height = 164.6 ± 6.9 cm; = 45 ± 8.6 mL O2 kg-1 min-1) were recruited. Participants completed physical exertion on a stationary cycle ergometer for simultaneous pulmonary minute ventilation ( ) measurements and EGAIC computations. Exercise protocols and subsequent conditions involved a 5-min cycling warm-up at 25 W min-1, incremental exercise to exhaustion ( ramp test), then a steady-state exercise bout induced by a constant Watt load equivalent to 80% ventilatory threshold (80% VT). A linear mixed model revealed that exercise intensity significantly affected measurements (p < 0.0001), whereas airflow sensor method (p = 0.97) and its interaction with exercise intensity (p = 0.91) did not. Group analysis of precision yielded a CV % = 21%; SEM = 5 mL O2 kg-1 min-1. Intra- and interindividual analysis of precision via Bland-Altman revealed a 95% confidence interval (CI) precision benchmark of 3-5 mL kg-1 min-1. Agreement among methods decreased at power outputs eliciting up to 150 L min-1, indicating a decrease in precision and highlighting potential challenges in interpreting biological variability, training response heterogeneity, and test-retest comparisons. These findings suggest careful consideration of airflow sensor method variance across metabolic cart configurations.

Flow sensing on dragonfly wings.

One feature of animal wings is their embedded mechanosensory system that can support flight control. Insect wings are particularly interesting as they are highly deformable yet the actuation is limited to the wing base. It is established that strain sensors on insect wings can directly mediate reflexive control; however, little is known about airflow sensing by insect wings. What information can flow sensors capture and how can flow sensing benefit flight control? Here, we use the dragonfly (Sympetrum striolatum) as a model to explore the function of wing sensory bristles in the context of flight control. Combining our detailed anatomical reconstructions of both the sensor microstructures and wing architecture, we used computational fluid dynamics simulations to ask the following questions. (1) Are there strategic locations on wings that sample flow for estimating aerodynamically relevant parameters such as the local effective angle of attack? (2) Is the sensory bristle distribution on dragonfly wings optimal for flow sensing? (3) What is the aerodynamic effect of microstructures found near the sensory bristles on dragonfly wings? We discuss the benefits of flow sensing for flexible wings and how the evolved sensor placement affects information encoding.

Rancang Bangun Sistem Transfer Liquid Berbasis Arduino Uno Menggunakan Sensor YF-S401

This article discusses the design of a liquid transfer system using a YF-S401 flow sensor and the evaluation of various calibration factors to create a reliable system. The research methods included water flow measurement, system component selection, system design, and workflow. The research results showed that a calibration factor of 50 was the optimal choice, showing good liquid transfer precision at a scale of 100 ml. However, testing at a scale of 200 ml and 300 ml showed suboptimal performance, especially in maintaining liquid transfer precision. Further development recommended in the selection of more reliable components, the improvement of the Arduino Uno program, and the implementation of technologies such as real time operating system (RTOS) to improve the accuracy of the liquid transfer system at larger scales. Overall, this research provides important insights for the development of automatic liquid transfer systems with a focus on precision in various measurement scales. Keywords—Liquid transfer system, Flow sensor, Calibration factor, Water flow measurement, Arduino Uno