Gauge Sensor Research Articles

Design Development of Punching and Bending Machine Combination

This paper purpose is to study working pressure limit of the machine combination between blanking and punching process. The combination punch and bending machine in this study is a machine that belongs to the press type with the use of punch and die. This machine has a hydraulic drive with a maximum pressure generated of 700 bars. The engine performance is only able to withstand a working pressure of 27.7 bars. Therefore, the utilization of the working pressure must be increased to maximize the working pressure. The analysis was carried out on the machine with two methods, namely simulation and experiment. The simulation method was carried out using Autodesk Inventor software to design and simulate in order to find out the critical points that occur on the machine. It was given working pressure according to the permitted safety factor of 1.5. The experimental method was carried out by measuring the voltage using a Strain gauge sensor positioned at the critical point obtained in the simulation and measuring the deflection using a dial indicator. From these tests, it was found that the initial working pressure before being optimized was 27.7 bars to 49.5 bars after being optimized.

Inkjet-Printed Flexible Strain-Gauge Sensor on Polymer Substrate: Topographical Analysis of Sensitivity

Inkjet-printed strain gauges on flexible substrates have recently been investigated for biomedical motion detection as well as the monitoring of structural deformation. This study performed a topographical analysis of an inkjet-printed strain gauge constructed using silver conductive ink on a PET (polyethylene terephthalate) substrate. Serpentine strain-gauge sensors of various thicknesses and widths were fabricated using inkjet printing and oven sintering. The fabricated gauge sensors were attached to curved surfaces, and gauge factors ranging from 2.047 to 3.098 were recorded. We found that the cross-sectional area of the printed strain gauge was proportional to the gauge factor. The correlation was mathematically modelled as y = 0.4167ln(x) + 1.3837, for which the coefficient of determination (R2) was 0.8383.

Numerical and Experimental Studies of Free-Fall Drop Impact Tests Using Strain Gauge, Piezoceramic, and Fiber Optic Sensors

The present work is framed inside a broader activity aimed at improving the accuracy of numerical models in predicting the crashworthiness behavior of flexible fuel tanks. This paper describes a comprehensive experimental and numerical study aimed at estimating the impact force of a test article, consisting of a soft nylon bag filled with water, subjected to crash impact tests. In order to understand and improve response predictions, the test article drops freely from different heights, and then strikes onto a rigid plate which is instrumented with different types of sensors. Strain gauges, piezoceramic sensors, and fiber optics are used to measure the strain induced by the impact force during the experiments. To tune the test matrix and the measurement chain parameters, numerical computations are carried out to predict the dynamics of drop impact through FE explicit analyses. Through analysis and comparison with experimental results, a relationship between strain and impact energy correlated with the drop height is established, and the overall accuracy of the entire measurement chain is assessed to determine the effectiveness of such a methodology in a full-scale test on a flexible fuel tank structure.

Local pressure calibration method of inductively coupled plasma generator based on laser Thomson scattering measurement

Based on laser Thomson scattering (TS) measurements and finite element method (FEM) simulations of electron density in inductively coupled plasma (ICP), the simulated local pressure calibration curves of ICP generator are obtained by comparing the experimental and simulated electron density distributions and maxima. The equation coefficients of theoretical model associated with the ICP generator experimental system can be obtained by fitting the simulation curve with the least square method, and the theoretical pressure calibration curves under different absorbed powers can be further obtained. Combined with the vacuum gauge measurements, both the simulated and theoretical pressure calibration curves can give the true local pressure in the plasma. The results of the local pressure calibration at the different absorbed powers show that the density gradient from the vacuum gauge sensor to the center of the coil in ICP generator cavity becomes larger with the increase of electron density, resulting in a larger gap between the measured value and the pressure calibration value. This calibration method helps to grasp the local pressure of ICP as an external control factor and helps to study the physicochemical mechanism of ICP in order to achieve higher performance in ICP etching, material modification, etc.

Adjustment of precipitation measurements using Total Rain weighing Sensor (TRwS) gauges in the cryospheric hydrometeorology observation (CHOICE) system of the Qilian Mountains, Northwest China

Adjustment of precipitation measurements using Total Rain weighing Sensor (TRwS) gauges in the cryospheric hydrometeorology observation (CHOICE) system of the Qilian Mountains, Northwest China

Maximum deflection of simple span steel box girder bridge using stress data

The Structural Health Monitoring System is part of tool and method for bridge operation and maintenance to make sure that the bridge is in good condition. Deflection is one of the main parameters to be measured and various methods has been introduced to measure deflection. Accuracy and economically are two main aspects when selecting the method for determine the real time deflection. This study presents a method of determining the maximum deflection of simple span continuous bridge using strain data obtained from a strain gauge sensor for simple span steel box girder bridge. Initial data were obtained from FEM simulations under various load conditions to obtain the maximum deflection value and the strain value. Linear regression and quadratic regression were carried out to obtain the relationship between the strains data and the maximum deflection. The accuracy of the maximum deflection value is then compared with the results of the analysis using FEM. It was found that the accuracy is about 91.16 % for quadratic regression and 9.07 for linear regression 90.93 %.

Моделювання варіантів транспедикулярної фіксації грудного відділу хребта при резекції одного-трьох хребців

Актуальність. Патологічні переломи хребців є найбільшим ускладненням пухлинного процесу. Застосування додаткової внутрішньої фіксації металевими імплантатами значно покращує результати лікування й скорочує строки реабілітації хворих. Використання транспедикулярних пристроїв забезпечує стабільну фіксацію й стабільність сегментів хребта навіть при максимальному ступені його нестабільності. Мета: визначення оптимального варіанта протяжності заднього спондилодезу при паліативному та радикальному хірургічному лікуванні пухлин хребта. Матеріали та методи. Для вивчення можливостей стабілізації за допомогою транспедикулярної фіксації при резекції одного-трьох хребців провели експериментальні випробування на препаратах хребта свині. Використовували препарати сегментів грудного відділу хребта від Th3 до Th12 хребців. Вивчали 3 групи моделей: з одним резектованим хребцем Th6, з двома — Th5-Th6 і з трьома — Th5-Th7. Результати. Виявлено, що при резекції одного хребця в грудному відділі хребта транс-педикулярна фіксація за схемами 111х111, 101х101 та 011х110 має однакову ефективність. При резекції двох хребців найкращі стабілізуючі можливості мала конструкція за схемою 111хх111, схеми 101хх101 та 011хх110 показали доволі непогану фіксуючу здатність. При резекції трьох хребців грудного відділу хребта найбільш стабільну фіксацію показала схема 111ххх111. Схема фіксації 001ххх100 виявилась нестабільною при всіх видах резекції хребців. Висновки. Експериментальні дослідження транспедикулярної фіксації при радикальному хірургічному лікуванні пухлин хребта, який включає резекцію одного-трьох хребців, показали, що конструкція відповідає вимогам фіксації, коли кріплення відбувається не менше ніж за два верхніх та два нижніх хребці (можна через один), при резекції трьох хребців найбільш стабільною є конструкція з кріпленням за три верхні та три нижні хребці (без пропусків). Система кріплення за один хребець виявилася неспроможною майже при всіх видах резекції.

Design, Simulation, Implementation and Measurement of Respiration Rate by Strain Gauge Sensor and Induction Method

The human body has vital parameters such as respiration, heart rate, and body temperature. Respiratory rate (RR) is a parameter that expresses the rate of respiration per minute. Respiratory activities play an essential role in human life. The rate of respiration has a particular range, which is 14-18 cycles per minute for a healthy and normal person at rest. The oxygen in the blood enters the body during respiration and is expelled as carbon dioxide in return. Any problems with breathing may pose a serious health risk. An abnormal breathing pattern indicates serious illnesses such as cardiac arrest and hospitalization in the intensive care unit (ICU) and when it falls below a certain limit, it indicates a loss of consciousness. This is why it is so imperative to develop devices and methods measuring respiration rates.

Days-ahead water level forecasting using artificial neural networks for watersheds.

Watersheds of tropical countries having only dry and wet seasons exhibit contrasting water level behaviour compared to countries having four seasons. With the changing climate, the ability to forecast the water level in watersheds enables decision-makers to come up with sound resource management interventions. This study presents a strategy for days-ahead water level forecasting models using an Artificial Neural Network (ANN) for watersheds by conducting data preparation of water level data captured from a Water Level Monitoring Station (WLMS) and two Automatic Rain Gauge (ARG) sensors divided into the two major seasons in the Philippines being implemented into multiple ANN models with different combinations of training algorithms, activation functions, and a number of hidden neurons. The implemented ANN model for the rainy season which is RPROP-Leaky ReLU produced a MAPE and RMSE of 6.731 and 0.00918, respectively, while the implemented ANN model for the dry season which is SCG-Leaky ReLU produced a MAPE and RMSE of 7.871 and 0.01045, respectively. By conducting appropriate water level data correction, data transformation, and ANN model implementation, the results of error computation and assessment shows the promising performance of ANN in days-ahead water level forecasting of watersheds among tropical countries.

Evaluation of strain measurements using ZnS: Mn, Cu as mechanoluminescent material and strain gauge sensor

Structural health monitoring (SHM) is emerging as a significant aspect in structural engineering. Predominantly, civil engineering structures have become more reliant on SHM. Advanced sensors and smart materials are the prominent technologies for applying Structural Health Monitoring. Numerous techniques for damage detection of the structures in the field of civil engineering. In this paper, we have introduced innovative smart material, Mechanoluminescent material that enables real-time continuous monitoring and damage detection of the structures. The most prominent ML (Mechanoluminescent material) Mn (Manganese) or Cu (Copper) doped ZnS (Zinc sulphide) crystal is studied because they exhibit the brightest luminescent emission. The present investigation aims to evaluate the strain measurements using ML material and compare the readings with the strain gauge sensor obtained in the Arduino Integrated Development Environment Software (IDE). An experimental approach has been done to produce ML material and to understand the fundamental ML phenomenon. At present, many researchers have developed ML material for the implementation to real-social infrastructure. If success leads the ML material will be a new step for development of modified sensor channel that could monitor a structure for actual impacts with the existence of stress levels acting on it.

Micro deformation measurement using flexible and ultra-thin glass sheet cantilever

Micromechanical characterization evaluation of single cells, such as elastic, young’s modulus and stiffness is of fundamental importance to the study of cell growth, differentiation, migration and morphogenesis. However, traditional methods (such as atomic force microscope or optical stretching methods) are time-consuming, complicated or low sensitivity. Device with the fast response and high sensitivity still remains challenging. Glass-based devices made of ultra-thin glass sheets are transparent and physically and chemically stable, which allows high resolution and real-time observation of cell deformability. Here a micro-indentation method using an ultra-thin glass sheet (UTGS) cantilever platform integrated with the metallic foil pattern as the strain gauge sensor provides a way to measure the micro deformation under 30 μm which could be used to measure the stiffness of single cells in the future.

Design a Building Information Modeling (BIM) project concept in combination with foundation monitoring on the example of the Abu Dhabi Plaza construction project

With the advent of new technology in the monitoring of buildings and highrise structures it has become possible to monitor damage and defects in existing structures and infrastructures. The need for timely detection of critical points of building structure defects through the use of sensors, as well as the lack of description tools for understanding, visualizing and documenting sensor output data increasingly encourages designers, builders and facility managers to use the capabilities of such a powerful system as the Building Information Modeling System (BIM). The primary goal of any construction project is safety for people, which can only be ensured by proper monitoring of building health, where the presentation and management of the received information about changes in the system and structure can be ensured by using BIM. The purpose of this paper is to describe the application of a distributed fiber optic strain gauge sensor system, and the possibility of integrating the data obtained from the sensors into the BIM system.

중형 유조선의 프로펠러 추력변동이 축 거동에 미치는 영향 연구

The movement of the propeller shaft shows different changes in each condition, such as static, dynamic, and transient, mainly based on changes in propeller eccentricity due to changes in engine load. In general, this contributes to changing the bearing load of the shaft at the after stern tube bearing, and in severe cases causes damage to the stern tube bearing. To prevent this, various research regarding pragmatic designing on shafting system has been carried out focusing on optimize the relative inclination and retain the oil film thickness between the shaft and the stern tube bearing. However, in order to secure the integrity of the support bearing from damage, it is necessary to additionally consider dynamic conditions including transient conditions such as sudden alteration in the stern wake-field. In this context, this study cross validated the effect of propeller shaft movement during starboard turning of a medium range oil tanker at full laden draft using the strain gauge and displacement sensor. As a result of the analysis, it was confirmed that the propeller thrust fluctuation temporarily increased the load on the stern tube bearing.

Machine Learning Methods for Automatic Silent Speech Recognition Using a Wearable Graphene Strain Gauge Sensor.

Silent speech recognition is the ability to recognise intended speech without audio information. Useful applications can be found in situations where sound waves are not produced or cannot be heard. Examples include speakers with physical voice impairments or environments in which audio transference is not reliable or secure. Developing a device which can detect non-auditory signals and map them to intended phonation could be used to develop a device to assist in such situations. In this work, we propose a graphene-based strain gauge sensor which can be worn on the throat and detect small muscle movements and vibrations. Machine learning algorithms then decode the non-audio signals and create a prediction on intended speech. The proposed strain gauge sensor is highly wearable, utilising graphene’s unique and beneficial properties including strength, flexibility and high conductivity. A highly flexible and wearable sensor able to pick up small throat movements is fabricated by screen printing graphene onto lycra fabric. A framework for interpreting this information is proposed which explores the use of several machine learning techniques to predict intended words from the signals. A dataset of 15 unique words and four movements, each with 20 repetitions, was developed and used for the training of the machine learning algorithms. The results demonstrate the ability for such sensors to be able to predict spoken words. We produced a word accuracy rate of 55% on the word dataset and 85% on the movements dataset. This work demonstrates a proof-of-concept for the viability of combining a highly wearable graphene strain gauge and machine leaning methods to automate silent speech recognition.

Experimental and Numerical Investigation of Bond-Slip Behavior of High-Strength Reinforced Concrete at Service Load

A bond mechanism at the reinforcement-concrete interface is one of the key sources of the comprehensive functioning of reinforced concrete (RC) structures. In order to apprehend the bond mechanism, the study on bond stress and slip relation (henceforth referred as bond-slip) is necessary. On this subject, experimental and numerical investigations were performed on short RC tensile specimens. A double pull-out test with pre-installed electrical strain gauge sensors inside the modified embedded rebar was performed in the experimental part. Numerically, a three dimensional rib scale model was designed and finite element analysis was performed. The compatibility and reliability of the numerical model was verified by comparing its strain result with an experimentally obtained one. Afterwards, based on stress transfer approach, the bond-slip relations were calculated from the extracted strain results. The maximum disparity between experimental and numerical investigation was found as 19.5% in case of strain data and 7% for the bond-slip relation at the highest load level (110 kN). Moreover, the bond-slip curves at different load levels were compared with the bond-slip model established in CEB-fib Model Code 2010 (MC2010). Overall, in the present study, strain monitoring through the experimental tool and finite element modelling have accomplished a broader picture of the bond mechanism at the reinforcement-concrete interface through their bond-slip relationship.

SMA AS MEANS FOR SENSITIVE BIOMEDICAL SENSORS

Shape memory alloys (SMA) are materials with specific electric, mechanic and thermal qualities originating in their microscopic structure and as such are used to design so-called Smart structures. In biomedicine, they are used mostly for their shape memory properties during intravasal surgery. The commonly used SMA material for biomedical purposes is Nitinol, a nickel-titanium alloy that exhibits, especially when annealed, among other properties also superelasticity and high resistivity with strain changes. This makes it suitable for usage in strain gauge sensors. In this work, NiTi annealed wires were used to create a strain gauge sensor, which exploits their unique properties. The properties of these sensors were then described using a climatic chamber, stretching device and a set of weights. Those properties were then compared to similar sensors, that are using different principles. The development, that followed, used these sensors in particular biomedical applications.

IoT-based Lava Flood Early Warning System with Rainfall Intensity Monitoring and Disaster Communication Technology

A lava flood disaster is a volcanic hazard that often occurs when heavy rains are happening at the top of a volcano. This flood carries volcanic material from upstream to downstream of the river, affecting populous areas located quite far from the volcano peak. Therefore, an advanced early warning system of cold lava floods is inarguably vital. This paper aims to present a reliable, remote, Early Warning System (EWS) specifically designed for lava flood detection, along with its disaster communication system. The proposed system consists of two main subsystems: lava flood detection and disaster communication systems. It utilizes a modified automatic rain gauge; a novel configured vibration sensor; Fuzzy Tree Decision algorithm; ESP microcontrollers that support IoT, and disaster communication tools (WhatsApp, SMS, radio communication). According to the experiment results, the prototype of rainfall detection using the tipping bucket rain gauge sensor can measure heavy and moderate rainfall intensities with 81.5% accuracy. Meanwhile, the prototype of earthquake vibration detection using a geophone sensor can remove noise from car vibrations with a Kalman filter and measure vibrations in high and medium intensity with an accuracy of 89.5%. Measurements from sensors are sent to the webserver. The disaster mitigation team uses data from the webserver to evacuate residents using the disaster communication method. The proposed system was successfully implemented in Mount Merapi, Indonesia, coordinated with the local Disaster Deduction Risk (DDR) forum. Doi: 10.28991/esj-2021-SP1-011 Full Text: PDF

Comparison of two data acquisition protocols for tide gauge sensors at Imbituba port – Santa Catarina State

The Santa Catarina Tide Gauge Network (SCTGN) is a continuous sea level monitoring system to support fishery, aquaculture, and navigation in general. Deployed in the state of Santa Catarina, Brazil, the initiative started in 2012 with one tide gauge at the Santa Catarina Island South Bay to support aquaculture research projects and hydrodynamic numerical modelling. By 2020, the SCTGN was fully operational, consisting of 11 tide gauge stations along the 450km of the Santa Catarina coastal line. The next step is standardizing these tide stations to international data collection protocols. Knowledge of the effects different programming protocols have on data collection are important since they may affect the results. Data from a radar gauge (RG) and a vented (or relative) pressure gauge (VPG) were obtained over six months. The difference between RG and VPG measurements showed a 5.07cm2 variance. Percentage of reading errors was 0.03% and 0.77% for RG and VPG, respectively. This study aims to evaluate the feasibility of the SCTGN data collection protocol in the RG to comply with the Intergovernmental Oceanographic Commission (IOC) recommendations for sea level monitoring. We find that an RG gauge using the SCTGN protocol is adequate to monitor sea levels and has an easier installation and maintenance, and more stable vertical datum control.

Design and implementation of the movement gauge for rail clearance based on combination measurement method

PurposeAs the infrastructure of the railway, the rail could sink or deform to different degrees due to the impact of train operation or the geological changing force for years, which will lead to the possibility that the facilities on both sides of the rail invade the rail clearance and bring hidden dangers to the safe operation of the train. The purpose of this paper is to design the gauge to measure the clearance parameters of rail.Design/methodology/approachAiming at the problem, the gauge for clearance measurement was designed based on a combination measurement method in this paper. It consists of the measurement box and the rail measurement vehicle, which integrates a laser displacement sensor, inclination sensor, gauge sensor and mileage sensor. The measurement box was placed outside the rail vehicle. Through the design of a hardware circuit and software system, the movement measurement of the clearance parameters was realized.FindingsIn this paper, the measurement equations of horizontal distance and vertical height were established, the optimal solutions of the structural parameters in the equations were obtained by Levenberg–Marquardt method, then the parameter calibration problem was also solved.Originality/valueThe gauge has high precision; its measurement uncertainty reaches 1.27 mm. The gauge has manual and automatic working modes, which are convenient to operate and have practical popularization value.

Dynamic Behavior of Pavement Layers on Sand Subgrade

Reinforcement interlayer reduces the development of cracks in the asphalt overlay by absorbing the stresses induced by heavy traffic or underlying cracking in the early-constructed pavement. This research is dedicated to studying the behavior of pavement layers on a sand subgrade under simulated effect of earthquake. In this study, the sand layer has a thickness of 600 mm and the base course is taken as 300 mm. The asphalt layer was prepared as a panel with dimensions of 300 × 300 × 50, which represents the surface layer. These layers are experimentally tested under the influence of earthquake loading with different frequencies 0.5, 1, 1.5 Hz. The tests consist of two parts without adding the geogrid, with geogrid in the center of the base layer and between the base layer and sand layer. Loaded stresses in the three layers are monitored using stress gauge sensors, while displacements of the asphalt layer by using displacement gauge sensor. Obtained results considered models reinforced with geogrid, the stress recorded is higher than in unreinforced models but the displacement decreases by increasing the geogrid in the layers at three frequencies. When the geogrid is laid between the base course and sand layer, the stress in the sand subgrade layer is less than that in the base and asphalt layers.