Sensor For Measurement Of Temperature Research Articles

Simultaneous bending and temperature measurement based on a superimposed fiber grating sensor

A compact and novel superimposed fiber grating (SI-FG) sensor for simultaneous measurement of temperature and bending based on UV-induced FBG cascaded with a multimode fiber (MMF) embedded ultra-long period fiber grating (MMF-EULPFG) has been proposed and experimentally validated. The MMF-EULPFG acts as a temperature and bending sensing unit and was fabricated by periodically splicing a non-UV-non-photosensitive MMF and a UV-photosensitive single-mode fiber (SMF) which is so called cleaving-splicing method. Due to the periodic refractive index modulation, the 6-period SMF-MMF structure based MMF-EULPFG with a total length of 2.7 mm forms transmission spectra with a −17 dB dip. The proposed SI-FG sensor exhibits high bending and temperature sensitivities of 17.096 nm/m−1 and −0.238 nm/℃, respectively. The UV-induced FBG is fabricated in the initial segment of UV-sensitive fibers within EULPFG by UV exposure method. The dip of FBG transmission spectra also shows response to bending and temperature. By utilizing a matrix obtained from the experimental results, simultaneous measurement of temperature and bending can be achieved. Due to its compact structure and high sensitivity, the proposed novel SI-FG sensor can be used as a competitive all-fiber sensor for structural health monitoring and 3D-shape sensing.Index Terms: Optical fiber sensor, long period fiber grating, superimposed fiber grating, simultaneous measure.

Tilted Bragg grating in a glycerol-infiltrated specialty optical fiber for temperature and strain measurements.

In this Letter, we propose an in-line tilted fiber Bragg grating sensor for temperature and strain measurements. The grating is inscribed in a specialty optical fiber using tightly focused femtosecond laser pulses and the line-by-line direct writing method. Beside the central core in which the grating is produced, a hollow channel filled with glycerol aqueous solution significantly improves the sensitivity of the fiber cladding modes due to its high thermo-optic coefficient. We show that the temperature sensitivity of the core mode is 9.8 pm/°C, while the one of the cladding modes is strongly altered and can reach -24.3 pm/°C, in the investigated range of 20-40°C. For the strain measurement, sensitivities of the core mode and the cladding modes are similar (∼0.60 pm/με) between 0 and 2400 με. The significative difference of temperature sensitivity between the two modes facilitates the discrimination of the dual parameters in simultaneous measurements.

Optical fiber sensor for curvature and temperature simultaneous measurement based on an anti-resonance mechanism

Based on an anti-resonance mechanism, we propose and experimentally demonstrate an optical fiber sensor for simultaneous measurement of curvature and temperature. The sensor structure consists of a hollow fiber and a twisted graded index multimode fiber spliced between two single-mode fibers. By using the twisted graded index multimode fiber to change the energy distribution of the mode field, not only improve the coupling efficiency of the sensor but also the sensitivity of the curvature measurement. The experimental results show that the intensity of the resonance peak based on the anti-resonance mechanism decreases with the increase of curvature, while the resonance peak wavelength is insensitive to curvature. In addition, due to the thermal expansion and thermo-optic effect of the fiber, the wavelength of the resonance peak is red-shifted with increasing temperature, and the intensity of the resonance peak is insensitive to temperature. Therefore, the intensity and wavelength signals of the resonance peak are monitored separately, and the simultaneous measurement of displacement and temperature is realized. The maximum sensitivity of the proposed curvature sensor can reach −2.84 dB/m−1, the dynamic range of curvature is 0 m−1 to 20.18 m−1, and the temperature sensitivity of 20 pm/∘C is realized. The proposed sensor has a compact structure, simple preparation, high coupling efficiency, and good repeatability, making it an ideal choice for simultaneous measurement of curvature and temperature in structural monitoring, mechanical manufacturing, and other fields.

A compact single-ended optical sensor for temperature measurements via laser absorption spectroscopy

The tunable diode laser absorption spectroscopy (TDLAS) has been employed in various fields successfully. However, most current TDLAS sensors have low spatial resolution, which is the inherent disadvantage of TDLAS techniques. To address this issue, a compact single-ended optical sensor based on the laser absorption spectroscopy is developed in this manuscript. The laser is delivered to the region of interest by a quartz rod, providing the sensor with millimeter-level spatial resolution. And the design of probe makes the singled-end sensor convenient and capable for measurements in diverse situations. In order to validate the feasibility of this structure, temperature of the flame produced with a McKenna burner is measured via absorption of H2O 7185.59 cm−1 and 7444.35 cm−1 transitions. Applying the scanned-wavelength modulation spectroscopy with second-harmonic detection and first-harmonic normalization (WMS-2f/1f) strategy, an enhancement of the signal-to-noise ratio over the short absorption path can be obtained. The temperature obtained by the single-ended sensor agrees well with that measured by a B-type thermocouple across different radial positions and heights, regardless of variations in equivalence ratios, confirming the accuracy of the sensor. In addition, a CFD simulation is performed to investigate the nonuniformity in the measurement region and the results show that the nonuniformity can be negligible.

Simultaneous measurement of refractive index and temperature using a balloon-type optical fiber sensor

In the food industry, acetic acid is a compound often used as a preservative or additive, but it is also produced during the fermentation of various food products and constitutes a key marker of food safety and quality. Although accurate, sensitive, and selective, the traditional methods for determining acetic acid are also expensive and time-consuming. In this regard, optical fiber sensors have emerged as a possible alternative for the real-time monitoring of small molecules. In this work, we propose an optical fiber sensor for the simultaneous measurement of refractive index (RI) and temperature using a balloon-shaped structure with a single sensing element. The sensor, based on cladding modal interference, was characterized by its response to RI in the range from 1.320 to 1.352 RIU, using acetic acid solutions with concentrations between 0% and 50%(v/v), and by its response to temperature between 23 and 43 °C. A maximum sensitivity of 170.66 nm/RIU was obtained for RI, equivalent to 110.7 pm/%(v/v) in terms of concentration, and a maximum sensitivity of −119.2 pm/°C was obtained for temperature.

120 kHz mid-infrared TDLAS sensor for H2O concentration and temperature measurement in rotating detonation engine exhaust flows

Rotating detonation engines (RDEs) require advanced rapid combustion diagnostic techniques to better understand their complex detonation processes. A fast mid-infrared TDLAS sensor was proposed to simultaneously monitor H2O concentration and temperature at the outlet of an H2/air-fueled RDE annular combustor. An iterative parameter extraction method from transmitted laser intensity was proposed to extract the H2O concentration and temperature of the detonation waves. A measurement rate of 120 kHz enables high-speed and simultaneous quantification of detonation wave combustions. The results show that when RDE operates stably, the detonation frequency, average temperature, and average molar percentage of H2O concentration of the detonation waves are 4.631 kHz, 1572.8 K, and 0.335, respectively. The detonation frequency extracted from H2O concentration and temperature is highly consistent with that extracted from thermal radiation, and the relative frequency error is only 0.022 %. The time-resolved H2O concentration and temperature data measured by the sensor accurately capture the thermal dynamics of the transient detonation waves.

Vapor bubble on a single nucleation site : Temperature and heat flux measurements

This work aimed at gaining a detailed understanding of heat transfer when boiling occurs on a heated substrate. More specifically, this work focuses on thermal transfers occurring at wall-fluid interfaces at the transition between natural convection and nucleate boiling regimes in pool boiling experiments. To avoid parasitic effects, the vapor bubble is created at a single artificial nucleation site. The boiling cell is instrumented with sensors for temperature measurement, pressure control, and parietal heat flux measurement. The fluid tested is Fluorinert FC-72. For providing a boiling surface and measuring heat flux, a boiling-meter consisting of a heating resistance, heat flux sensors and two thermocouples is used. This boiling-meter enables heat flux generation, the measurement of both temperature and heat flux, and can be rotated through 360°, enabling the influence of inclination to be studied. The boiling-meter is indented at its center to create a single vapor bubble. Thermal measurements are obtained and studied for different inclination angles between 0° and 180° at the saturation conditions. The results showed the nucleation site’s recurrent pattern of being active and inactive for whatever is the boiling surface inclination. Preliminary results are presented and discussed.

Personalized Weather Station

Abstract: This research outlines the conception, design, and implementation of a personalized weather monitoring system integrating multiple sensors for comprehensive environmental data collection. The project aims to create a sophisticated weather station utilizing the DHT11 sensor for temperature and humidity measurements, MQ135 sensor for gas detection, dust sensor for particulate matter assessment, and rain sensor for precipitation detection. The system's architecture incorporates Esp32-based data acquisition, employing sensor interfacing and data processing to obtain real-time environmental parameters. The project's significance lies in providing localized, accurate, and immediate weather insights beyond the capabilities of conventional smartphone applications.

Experimental study on ultra-high sensitivity gold-based SPR sensor for refractive index and temperature measurement

We have experimentally demonstrated an ultra-high sensitivity gold-based fiber refractive index (RI) sensor whose main structure is composed of multimode fiber (MMF) and photonic crystal fiber (PCF). The gold film is deposited on V-shaped PCF by magnetron sputtering, and sensing experiments are performed based on the principle of surface plasmon resonance (SPR). Numerical simulation results indicate that the cladding mode of the V-shaped PCF is more capable of stimulating the SPR effect than the core mode. The experimental results show that the RI measurement range of the sensor is 1.333–1.421, with a maximum sensitivity of 10015 nm/RIU. In addition to RI sensing, sensing probes can be coated with polydimethylsiloxane (PDMS) on a gold film for temperature sensing. For temperature detection, the range is from 10 to 100 °C and the maximum sensitivity is 3.5 nm/℃. Besides high sensitivity in RI measurement, the proposed sensor also has good sensing performance in temperature sensing. With the advantages of high sensitivity, good stability, and easy preparation, this sensor has become an important reference in the field of high-performance sensing.

Reflection based silicon incorporated silver coated fiber optic SPR sensor for refractive index and temperature measurement

Reflection based silicon incorporated silver coated fiber optic SPR sensor for refractive index and temperature measurement

All-sapphire fiber-optic sensor for the simultaneous measurement of ultra-high temperature and high pressure

An all-sapphire fiber-optic extrinsic Fabry-Perot interferometric (EFPI) sensor for the simultaneous measurement of ultra-high temperature and high pressure is proposed and experimentally demonstrated. The sensor is fabricated based on all-sapphire, including a sapphire fiber, a sapphire capillary and a sapphire wafer. A femtosecond (fs) laser is employed to drill a through hole at the side wall of the sapphire capillary to allow gas flow. The sapphire fiber is inserted from one side of the sapphire capillary. The sapphire wafer is fixed at the other side of the sapphire capillary. The first Fabry-Perot (FP) cavity, composed of the end face of the sapphire fiber and the front surface of the sapphire wafer, is used for measuring pressure, while the second FP cavity, composed of the two surfaces of the sapphire wafer, is used for measuring temperature. Experimental results show that the sensor can simultaneously measure ultra-high temperature and gas pressure within the temperature range of 20 - 1400 °C and the pressure range of 0 - 5 MPa. The temperature sensitivity is 0.0033 µm/°C, and the pressure sensitivity decreases as the temperature increases, reaching 1.8016 µm/MPa and 0.3253 µm/MPa at temperatures of 20 °C and 1400 °C, respectively.

IoT based weather monitoring system for temperature, humidity, rainfall and seismic detection in real time

This paper presents the design and implementation of an IoT-based weather monitoring system enhanced with seismic detection capabilities, employing Node MCU microcontroller and the Blynk mobile application platform. The system incorporates various sensors including a rain sensor, Light light-dependent resistor (LDR), a DHT11 sensor for temperature and humidity measurement, and an accelerometer (MPU6050) for earthquake detection. The hardware components are interconnected with the Node MCU microcontroller, facilitating real-time data acquisition from the sensors. Programming of the Node MCU is conducted using the Arduino IDE, enabling data transmission to the Blynk app via Wi-Fi connectivity. The Blynk app serves as the user interface, allowing seamless visualization and monitoring of weather parameters and seismic activity on smartphones. Key functionalities of the system include periodic data collection from sensors, transmission of sensor data to the Blynk server, and updating of graphical representations in the Blynk app interface. The accelerometer sensor is utilized to detect changes in acceleration, indicative of seismic disturbances. Threshold values are defined to trigger alerts within the Blynk app in the event of potential seismic activity. The implementation undergoes rigorous testing to ensure accuracy, reliability, and responsiveness under diverse environmental conditions. Considerations such as network stability, power efficiency, and data security are addressed to enhance system performance and longevity. The system demonstrates promising capabilities for real-time weather monitoring and seismic event detection, offering valuable insights for disaster preparedness and environmental analysis. IoT-based weather monitoring system integrated with seismic detection provides an effective solution for comprehensive environmental monitoring, leveraging the power of IoT technology and mobile applications for enhanced data accessibility and analysis. Further advancements and optimizations can be explored to extend the functionality and scalability of the system for broader applications in environmental science and disaster management.

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

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

Integrated All-Fiber Sensor for Simultaneous Measurements of Curvature and Temperature

Integrated All-Fiber Sensor for Simultaneous Measurements of Curvature and Temperature

Probe-Type Multi-Core Fiber Optic Sensor for Simultaneous Measurement of Seawater Salinity, Pressure, and Temperature.

In this article, we propose and demonstrate a probe-type multi-core fiber (MCF) sensor for the multi-parameter measurement of seawater. The sensor comprises an MCF and two capillary optical fibers (COFs) with distinct inner diameters, in which a 45° symmetric core reflection (SCR) structure and a step-like inner diameter capillary (SIDC) structure filled with polydimethylsiloxane (PDMS) are fabricated at the fiber end. The sensor is equipped with three channels for different measurements. The surface plasmon resonance (SPR) channel (CHSPR) based on the side-polished MCF is utilized for salinity measurement. The fiber end air cavity, forming the Fabry-Pérot interference (FPI) channel (CHFPI), is utilized for pressure and temperature measurement. Additionally, the fiber Bragg grating (FBG) channel (CHFBG), which is inscribed in the central core, serves as temperature compensation for the measurement results. By combining three sensing principles with space division multiplexing (SDM) technology, the sensor overcomes the common challenges faced by multi-parameter sensors, such as channel crosstalk and signal demodulation difficulties. The experimental results indicate that the sensor has sensitivities of 0.36 nm/‱, -10.62 nm/MPa, and -0.19 nm/°C for salinity, pressure, and temperature, respectively. As a highly integrated and easily demodulated probe-type optical fiber sensor, it can serve as a valuable reference for the development of multi-parameter fiber optic sensors.

Modeling analysis and experimental study on epoxy packaged FBG sensor for cryogenic temperature measurement

The Fiber Bragg grating (FBG) is a kind of temperature-sensitive optical device that has irreplaceable advantages for cryogenic measurement. In this work, a model-driven FBG temperature sensor packaging method was proposed to improve the sensor’s sensitivity and linearity and predict the sensor's response time in cryogenic. The numerical model explores the relationship between the sensor’s size and performance. The packaging method can prepare high-precision samples of multiple sizes and provide experimental support for this study. The accuracy of the model is verified by comparing the calculated results with the results of a warming-up experiment and a liquid nitrogen experiment. The results show an improvement in sensitivity and linearity, and the model can also be used to predict the characteristics of FBG coated with epoxy resins at cryogenic temperature. The sensor with a thickness of 0.2 mm has a sensitivity and linearity of 26.6 pm/K and 0.997, respectively, in the range of 80 K-270 K.

Bubble Sensors for Temperature Measurements through a Colorimetric Approach.

This paper introduces an innovative sensor utilizing bubbles coated with thermochromic paint, aiming to facilitate temperature measurements in challenging-to-reach locations without the requirement of an external power source. The research conducted is innovative in terms of both methodology and application. The characterization of the thermochromic properties of paints was, in fact, performed using spectroradiometric measurements by selecting a temperature range useful for applications in various fields including preventive conservation. The study encompasses two main objectives: (1) analyzing the color characteristics of thermochromic paint and plastic resin that forms the bubbles, and (2) assessing a temperature sensor comprising a thermochromic paint-coated bubble subjected to temperature variations. The thermochromic paint exhibits reversible color modifications in response to temperature changes, making it an ideal candidate for applications of this nature. The color characterization phase involves measurements using a spectroradiometer to compare the spectral reflectance factor (SRF%) of the colored plastic resin spread on canvas with that of the inflated bubbles. The sensor characterization entails evaluating color changes of the thermochromic paint on the bubble surface with varying temperatures. Experimental results indicate that the combination of a red (R) bubble and blue (B) thermochromic paint produces quantifiable color variations suitable for the proposed applications, whereas the alternative combination under examination, namely a blue bubble and red thermochromic paint, yields less accurate results. Considering that for both thermochromic paints the color change temperature is 35 °C, it is possible to see how, for B bubble with R thermochromic paint, the chromatic coordinates change value: C* = 3.14 ± 0.14 and h = 289.54 ± 11.58 at room temperature, while C* = 2.96 ± 0.12 and h = 304.20 ± 12.17 at 35 °C. The same is true for R bubble with B thermochromic paint where C* = 25.31 ± 1.01 and h* = 285.05 ± 11.40 at room temperature, while C* = 20.87 ± 0.85 and h = 288.37 ± 11.53 at 35 °C. The study demonstrates the potential of the approach and suggests further investigations into reproducibility and expanded color combinations. The results provide a promising basis for future improvements in temperature monitoring with thermochromic bubble sensors.

Monitoring and Controlling System of Smart Mini Greenhouse Based on Internet of Things (IoT) for Spinach Plant (Amaranthus sp.)

Greenhouses, often composed of plastic or glass structures, play a fundamental role in optimizing the environmental conditions essential for successful plant cultivation, ultimately resulting in higher-quality crop yields. The study aims to develop a real-time monitoring and control system for a smart mini greenhouse utilizing the Internet of Things (IoT), with a specific focus on cultivating spinach. The monitoring system is constructed around an ESP32 microcontroller, complemented by a DHT22 sensor for accurate air temperature and humidity measurements, and an RTC DS3231 timer for scheduling tasks. The DHT22 sensor's set point values trigger the fan and misting system operations. The fan activates when the air temperature reaches 32°C, while the misting system turns on when humidity levels (RH) reach 55%. The ESP32 is the central processing unit, enabling internet connectivity through Wi-Fi for real-time data monitoring via the Blynk application. Sensor calibration confirms the system's precision, with regression analyses producing impressive R2 values of 0.989 and 0.952. The shading net control system operates four hours daily, from 11:00 to 15:00 WIB (Western Indonesian Time), optimizing the greenhouse environment. This well-executed system leads to the robust growth of spinach plants, reaching a height of 23.02 cm, sprouting nine leaves, and attaining a weight of 10 grams. The findings from this study highlight the efficiency and effectiveness of the smart mini greenhouse's monitoring and control system, offering promising applications in broader greenhouse management and crop cultivation practices.

Design of a Meaningful Framework for Time Series Forecasting in Smart Buildings

This paper aims to provide discernment toward establishing a general framework, dedicated to data analysis and forecasting in smart buildings. It constitutes an industrial return of experience from an industrialist specializing in IoT supported by the academic world. With the necessary improvement of energy efficiency, discernment is paramount for facility managers to optimize daily operations and prioritize renovation work in the building sector. With the scale of buildings and the complexity of Heating, Ventilation, and Air Conditioning (HVAC) systems, the use of artificial intelligence is deemed the cheapest tool, holding the highest potential, even if it requires IoT sensors and a deluge of data to establish genuine models. However, the wide variety of buildings, users, and data hinders the development of industrial solutions, as specific studies often lack relevance to analyze other buildings, possibly with different types of data monitored. The relevance of the modeling can also disappear over time, as buildings are dynamic systems evolving with their use. In this paper, we propose to study the forecasting ability of the widely used Long Short-Term Memory (LSTM) network algorithm, which is well-designed for time series modeling, across an instrumented building. In this way, we considered the consistency of the performances for several issues as we compared to the cases with no prediction, which is lacking in the literature. The insight provided let us examine the quality of AI models and the quality of data needed in forecasting tasks. Finally, we deduced that efficient models and smart choices about data allow meaningful insight into developing time series modeling frameworks for smart buildings. For reproducibility concerns, we also provide our raw data, which came from one “real” smart building, as well as significant information regarding this building. In summary, our research aims to develop a methodology for exploring, analyzing, and modeling data from the smart buildings sector. Based on our experiment on forecasting temperature sensor measurements, we found that a bigger AI model (1) does not always imply a longer time in training and (2) can have little impact on accuracy and (3) using more features is tied to data processing order. We also observed that providing more data is irrelevant without a deep understanding of the problem physics.

Dual-Parameter Fiber Sensors for Salinity and Temperature Measurement Based on a Tapered PMF Incorporated With an FBG in Sagnac Loop

Dual-Parameter Fiber Sensors for Salinity and Temperature Measurement Based on a Tapered PMF Incorporated With an FBG in Sagnac Loop