Reflective Sensor Research Articles

Flattened fiber-optic ATR sensor enhanced by silver nanoparticles for glucose measurement.

This paper proposes a novel fiber attenuated total reflection (ATR) sensor with silver nanoparticles (AgNPs) on the flattened structure based on mid-infrared spectroscopy for detecting low concentration of glucose with high precision. The flattened structure was designed to add the effective optical path length to improve the sensitivity. AgNPs were then deposited on the surface of the flattened area of the fiber via chemical silver mirror reaction for further improving the sensitivity by enhancing the infrared absorption. Combining the AgNPs modified flattened fiber ATR sensor with a CO2 laser showed a strong mid-infrared glucose absorption, with an enhancement factor of 4.30. The glucose concentration could be obtained by a five-variable partial least-squares model with a root-mean-square error of 4.42mg/dL, which satisfies clinical requirements. Moreover, the fiber-based technique provides a pretty good method to fabricate miniaturized ATR sensors that are suitable to be integrated into a microfluidic chip for continuous glucose monitoring with high sensitivity.

Optical fiber Fresnel reflection sensor for direct detection of the solid–liquid phase change in n-octadecane

An all optical fiber Fresnel reflection sensor for detecting the solid–liquid phase change in n-octadecane is proposed and experimentally demonstrated. The sensor probe consists of a single-mode fiber with a cleaved end which is immersed in the material sample under test. As the n-octadecane changes from solid to liquid or from liquid to solid, its refractive index (RI) changes resulting in changes of the light power ratio reflected by the probe. Since the RI of n-octadecane during its phase transition changes discontinuously, inflection in the reflected light power ratio dependence indicates the phase change of the sample in the vicinity of the sensor probe. The results of this work suggest that such a simple optical fiber sensor can be used for detection of liquid–solid phase changes in other materials with similar to n-octadecane thermo-optic properties.

Improving an Active‐Optical Reflectance Sensor Algorithm Using Soil and Weather Information

Core Ideas Canopy sensor performance improved using site‐specific information. Evenness of early‐season rainfall is crucial for adjusting N recommendations. Adjusting N recommendations using measured vs. USDA mapped soil data performed alike Active‐optical reflectance sensors (AORS) use light reflectance characteristics from a crop canopy as an indicator of the plant’s N health. However, studies have shown AORS algorithms used in conjunction with measured reflectance characteristics for corn (Zea mays L.) N fertilizer rate recommendations are not consistently accurate. Our objective was to determine if soil and weather information could be utilized with an AORS algorithm developed at the University of Missouri (ALGMU) to improve in‐season (∼V9 corn development stage) N fertilizer recommendations. Nitrogen response trials were conducted across eight states over three growing seasons, totaling 49 sites with soils ranging in productivity. Nitrogen fertilizer rates according to the ALGMU were compared to economic optimal nitrogen rate (EONR). Without soil and weather information included, the root mean square error (RMSE) of the difference between ALGMU and EONR (MUDIFF) was 81 and 74 kg N ha−1 for treatments receiving 0 and 45 kg N ha−1 applied at planting, respectively. When ALGMU was adjusted using weather (seasonal precipitation and distribution prior to sidedress) and soil clay content, the RMSE was reduced by 24 to 26 kg N ha−1. Without adjustment, 20 and 29% of sites were within 34 kg N ha−1 of EONR with 0 and 45 kg N ha−1 at planting, respectively. But with adjustment for soil and weather data, 45 and 51% of sites were within 34 kg N ha−1 of EONR. These results show that weather and soil information could be used to improve ALGMU N recommendation performance.

Active‐Optical Reflectance Sensing Corn Algorithms Evaluated over the United States Midwest Corn Belt

Core Ideas Active‐optical reflectance sensor algorithms perform poorly outside the area for which they were originally developed. The red edge waveband is more sensitive to N stress than the red waveband. Some active‐optical reflectance algorithms are dependent on the sensor for which they were developed. Uncertainty exists with corn (Zea mays L.) N management due to year‐to‐year variation in crop N need, soil N supply, and N loss from leaching, volatilization, and denitrification. Active‐optical reflectance sensing (AORS) has proven effective in some fields for generating N fertilizer recommendations that improve N use efficiency, but locally derived (e.g., within a US state) AORS algorithms have not been tested simultaneously across a broad region. The objective of this research was to evaluate locally developed AORS algorithms across the US Midwest Corn Belt region for making in‐season corn N recommendations. Forty‐nine N response trials were conducted across eight states and three growing seasons. Reflectance measurements were collected and sidedress N rates (45–270 kg N ha−1 on 45 kg ha−1 increments) applied at approximately V9 corn development stage. Nitrogen recommendation rates from AORS algorithms were compared with the end‐of‐season calculated economic optimal N rate (EONR). No algorithm was within 34 kg N ha−1 of EONR > 50% of the time. Average recommendations differed from EONR 81 to 147 kg N ha−1 with no N applied at planting and 74 to 118 kg N ha−1 with 45 kg of N ha−1 at planting, indicating algorithms performed worse with no N applied at planting. With some algorithms, utilizing red edge instead of the red reflectance improved N recommendations. Results demonstrate AORS algorithms developed under a particular set of conditions may not, at least without modification, perform very well in regions outside those within which they were developed.

Unity Integration of Grating Slot Waveguide and Microfluid for Terahertz Sensing

AbstractRefractive index sensing is attracting extensive interest. Limited by the weak light–matter interaction and the broad bandwidth of resonance, the figure of merit (FoM) of terahertz (THz) sensors is much lower than their counterparts in visible and infrared regions. Here, these two issues are addressed by incorporating a microfluidic channel as a slot layer into a grating slot waveguide (GSW), where guided‐mode resonance results in a narrowband resonant peak and the sensitivity increases remarkably due to the greatly concentrated electromagnetic fields in the slot layer. Both reflective and transmissive sensors are developed with the calculated quality (Q) factors two orders of magnitude larger than metamaterial and plasmonic sensors, and the sensitivities one order of magnitude larger than grating waveguide sensors, contributing to a record high FoM of 692. The measured results match well with the simulations considering the fabrication errors, where the degeneration of narrowband transmission peaks in experiments is attributed to the error of the microfluidic channel height and the divergence of the incident beam. The proposed unity‐integrating configuration with simultaneous optimizations of the resonance mechanism, and the spatial overlap between the sensing field and the analytes shows the potential for high sensitivity bio and chemo sensing.

Optical Fiber Tip Sensor for the Measurement of Glucose Aqueous Solutions

A reflective fiber optic sensor based on multimode interference for the measurement of refractive index variations in glucose aqueous solutions is proposed. The sensor is fabricated by splicing a short section of coreless silica fiber to standard single mode fiber. The influence of the coreless fiber dimensions on the sensor performance is analyzed. By changing the sensor length, no significant impact is observed. However, the reduction of the sensing head diameter leads to a large improvement of the sensitivity. The smaller sensor, with a length of 5 mm and a diameter of 24 μm, presents a maximum sensitivity of 1467.59 nm/RIU, for the refractive index range between 1.364 and 1.397 RIU. Taking into account the acquisition system, a maximum theoretical resolution of 6.8 × 10 -5 RIU is achieved.

Preparation and characterization Co3O4 nanoparticles on porous silicon for humidity sensor by photoluminescence

Porous silicon (PS) has attracted considerable attention as potential materials for gas/vapor sensing because of very high surface to volume ratio. PS with some metals such as Co3O4 is necessary to create and provide new nanocomposite materials with new properties that combine semiconducting and magnetic properties. In the present work, the samples to be studied were characterized from atomic force microscope (AFM), X-ray diffraction (XRD), reflectivity, photoluminescence (PL) spectra and humidity sensor. X-ray diffraction for PS in the range of 20°-70° at 2 theta, show an important peak at 28.35◦ oriented (111), while the Co3O4/PS have four characteristic peaks at 36.758°, 44.738°, 59.177° and 64.980°, were corresponding to the oriented (311), (222), (511) and (440) respectively. PL test for PS/Co3O4 shows a slightly less intensity and slight change in location in case of PS due to Co3O4 NPs granular size which acts as a cover, thus reducing the surface area of the PS which reduces PL. In PS/Co3O4 sample shows that the PL spectra peak is different from PS at shape and the effect of relative humidity (RH) at this peak due to the decrease of intensity at peak. Through these results we conclude that PS/Co3O4 can be used as sensor humidity.

Optimization of a quantum weak measurement system with digital filtering technology.

In this paper, we propose a post-Gaussian filtering theory for weak measurement in the frequency domain, and propose a highly deformed digital filtering technique that can be used to optimize sensors based on weak-frequency measurement techniques. We completed the experimental verification based on the weak measurement total internal reflection sensor. The experimental results show that digital filtering technology can optimize the system in the working range, sensitivity, and resolution of the frequency domain weak measurement system, so that it can reach 0.210rad, 3210.9nm/RIU, and 7.12×10-7 RIU, respectively.

Design, Fabrication and Testing of a High-Sensitive Fibre Sensor for Tip Clearance Measurements.

A highly sensitive fibre bundle-based reflective optical sensor has been designed and fabricated for Tip Clearance measurements in a turbine rig. The sensor offers high spatial and temporal resolution. The sensor probe consists of a single-mode transmitting fibre and two concentric rings of receiving multimode fibres that collect reflected light in a differential detection gain configuration, yielding a highly linear calibration curve for distance measurements. The clearance measurement range is approximately 2 mm around the central point fixed at 3.2 mm from the probe tip, and the sensitivity of the probe is 61.73 mm−1. The fibre bundle has been designed to ensure that the distance security specifications required for the experimental program of the turbine are met. The optical sensor has operated under demanding conditions set by the blade and casing design. The experimental results obtained so far are promising and lead us to think that the optical sensor has great potential for online clearance measurements with high precision.

Spatial Division Multiplexing-Based Reflective Intensity-Modulated Fiber Optics Displacement Sensor

Due to the benefit of multiple parallel channels within single cladding and easy implementation of multi-input multioutput technique, we present the spatial division multiplexing (SDM)-based reflective intensity-modulated fiber optics displacement sensor (RIMFODS). Under the condition of single-input single-output, we experimentally compare the transfer function of RIMFODS by using a pair of standard single-mode fibers (SSMFs), single seven-core-single-mode fiber, and single seven-core-few-mode fiber. In comparison with the conventional SSMF-based RIMFODS, the use of seven-core-few-mode fiber can reduce the dead zone of measurement range from 200 to 100 μ m. Meanwhile, the system sensitivity can be enhanced from 0.14 to 12.2 nW/ μ m. In particular, with the help of two-input-five-output technique, the dead zone can be further reduced to 70 μ m, with sensitivity reaching as high as 53.87 nW/ μ m. Finally, we theoretically investigate the effect of both the core size and the core spacing of multicore fiber on the transfer function of RIMFODS. Such an SDM-based RIMFODS with compact footprint has lots of potential to be exploited.

The Safety Rotor—An Electromechanical Rotor Safety System for Drones

We propose a novel rotor safety mechanism for rotary-wing small unmanned aerial vehicles, such as quadrotors, that avoids problems associated with cages, rotor shrouds, and obstacle avoidance safety systems. The system works by using a passively spinning hoop as a mechanical interference sensor; changes in hoop speed are detected with a reflective IR sensor, which triggers an electrodynamic braking circuit. Experiments demonstrated that the system can rapidly detect incipient collisions and bring the rotors of a retrofitted DJI Phantom 3 to a halt from flight speed within 0.06 s of contact. In testing with finger proxies and surface collisions, the safety rotor provided an effective mechanism for reducing the severity of rotor injuries during impact.

Proximal Optical Sensors for Nitrogen Management of Vegetable Crops: A Review.

Optimal nitrogen (N) management is essential for profitable vegetable crop production and to minimize N losses to the environment that are a consequence of an excessive N supply. Proximal optical sensors placed in contact with or close to the crop can provide a rapid assessment of a crop N status. Three types of proximal optical sensors (chlorophyll meters, canopy reflectance sensors, and fluorescence-based flavonols meters) for monitoring the crop N status of vegetable crops are reviewed, addressing practical caveats and sampling considerations and evaluating the practical use of these sensors for crop N management. Research over recent decades has shown strong relationships between optical sensor measurements, and different measures of crop N status and of yield of vegetable species. However, the availability of both: (a) Sufficiency values to assess crop N status and (b) algorithms to translate sensor measurements into N fertilizer recommendations are limited for vegetable crops. Optical sensors have potential for N management of vegetable crops. However, research should go beyond merely diagnosing crop N status. Research should now focus on the determination of practical fertilization recommendations. It is envisaged that the increasing environmental and societal pressure on sustainable crop N management will stimulate progress in this area.

Sleep stage detection using a wristwatch-type physiological sensing device

Here, we propose an automated sleep stage classification method using a wristwatch-type physiological sensing device including a reflective photoelectric volume pulse sensor and a three-axis accelerometer to allow simple and inexpensive assessment of sleep quality. One hundred healthy volunteers (60 males and 40 females, aged 20–60 years old) wore the wristwatch-type physiological sensing device during overnight full polysomnography (PSG). Pulse-to-pulse intervals (PPI) and body movement indexes were determined from the records of the sensing device. The features extracted from the time-domain measures of PPI together with wrist movement indexes were utilized to develop an automated sleep stage classification system. The sleep stages detected by the proposed algorithm were compared with those determined by PSG utilizing the standard performance metrics (accuracy, recall, precision and F-measure). The mean rates of agreement with sleep stages on PSG categorized into two stages (wake and sleep), three stages (wake, non-REM, REM), and four stages (wake, light, and deep non-REM, REM) were 87.3, 74.3, and 68.5%, respectively. The accuracy of sleep stage detection indicated that the proposed method was sufficient for assessing sleep quality in healthy subjects without sleep disorders, and the wristwatch-type sensing device developed here can be used as a portable and easy-to-use home sleep monitoring device.

Reflective mercury ion and temperature sensor based on a functionalized no-core fiber combined with a fiber Bragg grating

A reflective fiber optic sensor is proposed and experimentally validated, which enables simultaneous measurement of temperature and mercury ion (Hg2+) concentration. The sensor consists of a fiber Bragg grating (FBG) and a functionalized no-core fiber (NCF). The chitosan (CS)/poly acrylic acid (PAA), as Hg2+ sensitive film, is assembled on the surface of the NCF by layer-by-layer self-assembly method. Besides, the silver film is coated on the end of NCF to ensure the reflection of light. This reflective fiber structure forms a fiber modal interferometer. When the sensor is immersed in the test solution, the Hg2+ adsorption of sensitive film leads to change in its refractive index, and then the interference spectrum of the fiber modal interferometer will shift accordingly, which is the measurement principle of Hg2+ sensor. Meanwhile, when the surrounding temperature changes, the interference fringe of the fiber modal interferometer and the Bragg wavelength of FBG will shift simultaneously. Therefore, the Hg2+ concentration and temperature can be simultaneously measured by using dual-wavelength matrix method, and then the cross sensitivity problem of temperature and Hg2+ concentration can also be solved. The experimental results show that the detection sensitivity of Hg2+ concentration is 0.0823 nm/μM in the range of 0 μM–100 μM and 0.0178 nm/μM in the range of 100 μM–500 μM, respectively. The temperature sensitivity is 0.0147 nm/°C in the range of 20 °C–50 °C.

Reader Architectures for Wireless Surface Acoustic Wave Sensors.

Wireless surface acoustic wave (SAW) sensors have some unique features that make them promising for industrial metrology. Their decisive advantage lies in their purely passive operation and the wireless readout capability allowing the installation also at particularly inaccessible locations. Furthermore, they are small, low-cost and rugged components on highly stable substrate materials and thus particularly suited for harsh environments. Nevertheless, a sensor itself does not carry out any measurement but always requires a suitable excitation and interrogation circuit: a reader. A variety of different architectures have been presented and investigated up to now. This review paper gives a comprehensive survey of the present state of reader architectures such as time domain sampling (TDS), frequency domain sampling (FDS) and hybrid concepts for both SAW resonators and reflective SAW delay line sensors. Furthermore, critical performance parameters such as measurement accuracy, dynamic range, update rate, and hardware costs of the state of the art in science and industry are presented, compared and discussed.

Differential photoplethysmogram sensor with an optical notch filter shows potential for reducing motion artifact signals

Objective: Photoplethysmography (PPG) has become the standard technology used in wearable health and fitness monitoring devices. Although, PPG works well at rest, trying to incorporate it for continuous monitoring is challenging, since the signal is inevitably corrupted by motion artifacts. This paper explores the feasibility of a reflective PPG sensor aiming at reducing the changes caused by motion in the non-pulsatile component of the signal, e.g., changes in venous filling. Approach: The tested sensor consisted of two back-to-back connected photodiodes and a light source with a peak wavelength around 575 nm. Additionally, the second photodiode was covered by a 575 ± 5 nm optical notch filter. Main results: When compared to standard PPG (single detector) on one test subject, the tested sensor provided 4.38 dB of attenuation for a change in venous blood during a gentle lift of upper extremity. Moreover, over 40 dB rejection was measured in the baseline resulting in a very small ‘direct current’ (DC) component. Furthermore, the baseline wander due to respiratory modulation tended to be smaller for the tested sensor. The sensor was not either susceptible for the changes in ambient light or the drift caused by the light source heating up. Significance: We believe that this is the first work that proposes the back-to-back connected photodiodes and a notch filter to reduce in-band noise in PPG. The positive results encourage to further optimize and integrate the sensor. The novelty of the method also brings new perspective to the PPG measurements.

Development of a compact optical torque sensor with decoupling axial-interference effects for pHRI

This paper presents the design of an optical torque sensor that can structurally decouple the effect of axial-interference for use in various robotics applications. Torque sensors are widely used in the joints of intelligent service or wearable robots to realize safe human-robot interaction. Whole robot body sensing using torque sensors is essential for safe interaction. However, most torque sensors are bulky, heavy and expensive. Therefore, many optical-based torque sensors have been proposed to deal with such problems, but the issue of axial-interference still remains. We resolved the axial-interference problem via the geometrical structure of the sensor body and differential signaling using two reflective optical sensors. The moment interference error was successfully decreased from 4.49% (with one optical sensor) to 0.11% (with two optical sensors) using the proposed sensor structure while maintaining a compact size, lightweight, and low cost. Static tests and dynamic tests were carried out and analyzed for accuracy error, hysteresis, and repeatability. We then compared the performance of an impedance controller that is widely used in service and wearable robots using the proposed sensor and a commercial torque sensor with respect to various control loop rates. The control performance of the proposed sensor was comparable to that of commercial sensors.

A reflective hydrogen sensor based on fiber ring laser with PCF modal interferometer

A new hydrogen sensor based on a fiber ring laser with a photonic crystal fiber (PCF) modal interferometer is proposed. The reflective PCF modal interferometer, which is fabricated by forming two collapse regions on the two ends of PCF with a fusion discharge technique, is utilized as the sensing head and filter. Particularly, the Pd/WO3 hydrogen-sensitive thin film is coated on the PCF for hydrogen sensing. The combination of the fiber ring laser and PCF modal interferometer gives the sensor a high signal-to-noise ratio and an improved detection limit. Experimental results show that the sensing system can achieve a hydrogen sensitivity of 1.28 nm/%, a high signal-to-noise ratio (∼30 dB), a narrow full width at half maximum (∼0.05 nm), and low detection limit of 0.0133%.

Deploying a Proximal Sensing Cart to Identify Drought-Adaptive Traits in Upland Cotton for High-Throughput Phenotyping.

Field-based high-throughput phenotyping is an emerging approach to quantify difficult, time-sensitive plant traits in relevant growing conditions. Proximal sensing carts represent an alternative platform to more costly high-clearance tractors for phenotyping dynamic traits in the field. A proximal sensing cart and specifically a deployment protocol, were developed to phenotype traits related to drought tolerance in the field. The cart-sensor package included an infrared thermometer, ultrasonic transducer, multi-spectral reflectance sensor, weather station, and RGB cameras. The cart deployment protocol was evaluated on 35 upland cotton (Gossypium hirsutum L.) entries grown in 2017 at Maricopa, AZ, United States. Experimental plots were grown under well-watered and water-limited conditions using a (0,1) alpha lattice design and evaluated in June and July. Total collection time of the 0.87 hectare field averaged 2 h and 27 min and produced 50.7 MB and 45.7 GB of data from the sensors and RGB cameras, respectively. Canopy temperature, crop water stress index (CWSI), canopy height, normalized difference vegetative index (NDVI), and leaf area index (LAI) differed among entries and showed an interaction with the water regime (p < 0.05). Broad-sense heritability (H2) estimates ranged from 0.097 to 0.574 across all phenotypes and collections. Canopy cover estimated from RGB images increased with counts of established plants (r = 0.747, p = 0.033). Based on the cart-derived phenotypes, three entries were found to have improved drought-adaptive traits compared to a local adapted cultivar. These results indicate that the deployment protocol developed for the cart and sensor package can measure multiple traits rapidly and accurately to characterize complex plant traits under drought conditions.

Prediction Models for Assessing Lycopene in Open-Field Cultivated Tomatoes by Means of a Portable Reflectance Sensor: Cultivar and Growing-Season Effects.

Reflectance spectroscopy represents a useful tool for the nondestructive assessment of tomato lycopene, even in the field. For this reason, a compact, low-cost, light emitting diode-based sensor has been developed to measure reflectance in the 400-750 nm spectral range. It was calibrated against wet chemistry and evaluated by partial least squares (PLS) regression analyses. The lycopene prediction models were defined for two open-field cultivated red-tomato varieties: the processing oblong tomatoes of the cv. Calista (average weight: 76 g) and the fresh-consumption round tomatoes of the cv. Volna (average weight: 130 g), over a period of two consecutive years. The lycopene prediction models were dependent on both cultivar and season. The lycopene root mean square error of prediction produced by the 2014 single-cultivar calibrations validated on the 2015 samples was large (33 mg kg-1) in the Calista tomatoes and acceptable (9.5 mg kg-1) in the Volna tomatoes. A more general bicultivar and biyear model could still explain almost 80% of the predicted lycopene variance, with a relative error in red tomatoes of less than 20%. In 2016, the in-field applications of the multiseasonal prediction models, built with the 2014 and 2015 data, showed significant ( P < 0.001) differences in the average lycopene estimated in the crop on two sampling dates that were 20 days apart: on August 19 and September 7, 2016, the lycopene was 98.9 ± 9.3 and 92.2 ± 10.8 mg kg-1 FW for cv. Calista and 54.6 ± 13.2 and 60.8 ± 6.8 mg kg-1 FW for cv. Volna. The sensor was also able to monitor the temporal evolution of lycopene accumulation on the very same fruits attached to the plants. These results indicated that a simple, compact reflectance device and PLS analysis could provide adequately precise and robust (through-seasons) models for the nondestructive assessment of lycopene in whole tomatoes. This technique could guarantee tomatoes with the highest nutraceutical value from the production, during storage and distribution, and finally to consumers.