Non-contact Sensor Research Articles

A Flexible Self-Powered Noncontact Sensor with an Ultrawide Sensing Range for Human-Machine Interactions in Harsh Environments.

Noncontact human-machine interactions (HMIs) provide a hygienic and intelligent approach to communicate between humans and machines. However, current noncontact HMIs are generally hampered by the interaction distance, and they lack the adaptability to environmental interference such as high humidity conditions. Here, we explore a self-powered electret-based noncontact sensor (ENS) with moisture-resisting ability and ultrawide sensing range exceeding 2.5 m. A megascopic air-bubble structure is designed to enhance charge-storage stability and charge-recovery ability of the ENS based on the heterocharge-synergy effect in electrets. Besides, multilayer electret films are introduced to strengthen the electric field by utilizing the electrostatic field superposition effect. Thanks to the above improved performances of the ENS, we demonstrate various noncontact HMI applications in harsh environments, including noncontact appliances, a moving trajectory and accidental fall tracking system, and a real-time machine learning-assisted gesture recognition system with accuracy as high as 99.21%. This research expands the way for noncontact sensor design and may further broaden applications in noncontact HMIs.

3D vibration modes estimation of complex-shaped structure by Phase-based motion magnification and DIC method

Knowing the 3D mode shapes of a structure is important in solving unwanted vibration and noise problems in mechanical systems. Accordingly, various analysis methods for estimating the vibration modes of complex-shaped structures have been proposed. However, it is difficult to attach accelerometers to a complex-shaped structure, and to cover a large area, many accelerometers must be attached. So experimental verification of the mode shapes of an actual structure is insufficient. Therefore, the purpose of this study is to experimentally estimate the 3D vibration modes of a complex structure using two cameras by Phase-based image magnification and DIC method. In addition, by using non-contact sensor such as a camera, it is possible to estimate the modes without affecting the mass or stiffness of the structure.

Contactless Heart and Respiration Rates Estimation and Classification of Driver Physiological States Using CW Radar and Temporal Neural Networks

The measurement and analysis of vital signs are a subject of significant research interest, particularly for monitoring the driver’s physiological state, which is of crucial importance for road safety. Various approaches have been proposed using contact techniques to measure vital signs. However, all of these methods are invasive and cumbersome for the driver. This paper proposes using a non-contact sensor based on continuous wave (CW) radar at 24 GHz to measure vital signs. We associate these measurements with distinct temporal neural networks to analyze the signals to detect and extract heart and respiration rates as well as classify the physiological state of the driver. This approach offers robust performance in estimating the exact values of heart and respiration rates and in classifying the driver’s physiological state. It is non-invasive and requires no physical contact with the driver, making it particularly practical and safe. The results presented in this paper, derived from the use of a 1D Convolutional Neural Network (1D-CNN), a Temporal Convolutional Network (TCN), a Recurrent Neural Network particularly the Bidirectional Long Short-Term Memory (Bi-LSTM), and a Convolutional Recurrent Neural Network (CRNN). Among these, the CRNN emerged as the most effective Deep Learning approach for vital signal analysis.

High Stability Dual Beam Interferometer Sensor for Non-contact Photoacoustic Imaging

As a non-contact photoacoustic sensor, the reflector of one arm of dual beam interferometer sensor is usually composed of the upper surface of the ultrasonic coupling liquid coated on the surface of the sample. The vibration of the outside and the scanning motor cause the liquid level to shake, causing the reflected probe light path to deviate from the incident light path, which then reduces the detection stability of the sensor. In view of the above problems, a novel high stability dual beam interferometer sensor is introduced in this paper, in which the reflected probe light is derived from the original optical path by using the combination of PBS and quarter wave plate, and the reflected probe light is coupled into 50/50 beam splitting fibre by using aspheric mirror group. The influence of the radius and focal length of each aspheric mirror and the numerical aperture of the optical fibre on the detection stability of the sensor is theoretically analyzed. The results show that the structural design greatly reduces the effect of the vibration of the outside and the scanning motor on the detection stability of the sensor, and provides a theoretical basis for the development and performance optimization of the sensor.

Highly Responsive, Miniaturized Methane Telemetry Sensor Based on Open-Path TDLAS

This paper proposes the design of a highly responsive, compact, non-contact methane telemetry sensor, employing the open-path tunable diode laser absorption spectroscopy (OP-TDLAS) technology. The sensor uses the dual-core structure of FPGA and ARM to achieve high-speed methane telemetry at 100 KHz repeated modulation frequency for the first time with a non-cooperate target, and a higher gas responsive time of 1.8 ms was achieved than previously reported. Moreover, the optical system (L × W × H: 68.8 × 52 × 62.7 mm) and the electronic system (L × W: 70 × 50 mm) make the sensor more compact. Methane gas samples of varying integral concentrations were examined at a distance of 20 m. The amplitude of the absorption peaks was subjected to a linear fit with the standard concentration values, resulting in a robust linear correlation coefficient (R2 = 0.998). Notably, despite the compact form factor of the methane sensor, it demonstrated commendable stability in gas concentration detection, offering a minimum detection limit of 43.14 ppm·m. Consequently, this highly responsive and compact methane sensor, with its open-path feature, is apt for integration into a variety of applications requiring such attributes. These include handheld telemetry devices, Unmanned Aerial Vehicle (UAV) gas detection systems, vehicle mounted gas detection, and laser gas radar.

Using a Non-Contact Sensor to Delineate Management Zones in Vineyards and Validation with the Rasch Model.

The production of high-quality wines is one of the primary goals of modern oenology. In this regard, it is known that the potential quality of a wine begins to be determined in the vineyard, where the quality of the grape, initially, and later that of the wine, will be influenced by the soil properties. Given the spatial variability of the fundamental soil properties related to the potential grape production, such as texture, soil organic matter content, or cation exchange capacity, it seems that a uniform management of a vineyard is not the most optimal way to achieve higher grape quality. In this sense, the delineation of zones with similar soil characteristics to implement site-specific management is essential, reinforcing the interest in incorporating technologies and methods to determine these homogeneous zones. A case study was conducted in a 3.3 ha vineyard located near Évora, south of Portugal. A non-contact sensor (DUALEM 1S) was used to measure soil apparent electrical conductivity (ECa) in the vineyard, and later, a kriged ECa map was generated. ECa and elevation maps were utilised to delineate homogeneous zones (management zones, MZs) in the field through a clustering process. MZs were validated using some soil properties (texture; pH; organic matter-OM; phosphorous-P2O5; potassium-K2O; the sum of the exchange bases-SEB; and cation exchange capacity-CEC), which were determined from 20 soil samples taken in the different MZs. Validation was also performed using Rasch measures, which were defined based on the formulation of the objective and probabilistic Rasch model, integrating the information from the aforementioned soil properties at each sampling location. The comparison of the MZs was more evident with the use of the Rasch model, as only one value was to be employed in each MZ. Finally, an additional validation was conducted using a vegetation index to consider the plant response, which was different in each MZ. The use of a non-contact sensor to measure ECa constitutes an efficient technological tool for implementing site-specific management in viticulture, which allows for the improvement of decision-making processes by considering the inherent spatial variability of the soil.

Dynamic Characterization of Optical Coherence-Based Displacement-Type Weight Sensor

Dynamic characteristics play a crucial role in evaluating the performance of weight sensors and are essential for achieving fast and accurate weight measurements. This study focuses on a weight sensor based on optical coherence displacement. Using finite element analysis, the sensor was numerically simulated. Frequency domain and time domain dynamic response characteristics were explored through harmonic response analysis and transient dynamic analysis. The superior dynamic performance and reduced conditioning time of the non-contact optical coherence-based displacement weight sensor were confirmed via a negative step response experiment that compared the proposed sensing method to strain sensing. Moreover, dynamic performance metrics for the optical coherence displacement-type weight sensor were determined. Ultimately, the sensor’s dynamic performance was enhanced using the pole-zero placement method, decreasing the overshoot to 4.72% and reducing the response time to 0.0132 s. These enhancements broaden the sensor’s operational bandwidth and amplify its dynamic response capabilities.

Online Monitoring of Cable Insulation Degradation for Inverter-Fed Machine System Using PWM Switching Oscillations

Online cable condition monitoring is a reliability enhancement technique for inverter-fed machine systems, which requires high sensitivity with quantitative assessment capability to detect the incipient insulation degradation as early as possible. This article presents a noncontact cable condition monitoring method by utilizing the inverter's self-excited high-frequency (HF) PWM switching oscillations. As an HF resonance, the switching oscillation is sensitive to the small change of degrading cable insulation capacitance. First, the characteristic mode, i.e. the HF differential-mode, is selected for sensitive cable condition monitoring from the multi-modal switching oscillation in an inverter-fed machine system. Then, an online condition monitoring scheme is proposed, including the framework, the noncontact HF oscillation current sensor, and the indicator(s) of cable insulation condition estimated from the amplitude-frequency features of the characteristic oscillation mode. Finally, experimental work was carried out on a 20 m cable-connected 3-kW inverter-fed machine test rig and the results demonstrate the good sensitivity and robustness of the method.

Web-based Non-contact Edge Computing Solution for Suspected COVID-19 Infection Classification Model

The recent outbreak of the COVID-19 coronavirus pandemic has necessitated the development of web-based, non-contact edge analytics solutions. Non-contact sensors serve as the interface between web servers and edge analytics through web engineering technology. The need for an edge device classification model that can identify COVID-19 patients based on early symptoms has become evident. In particular a non-contact implementation of such a classification model is required to efficiently prevent viral infection and minimize cross-infection. In this work, we investigate the use of diverse non-contact biosensors (e.g., remote photoplethysmography, radar, and infrared sensors) for reducing effective physical contact with patients and for measuring their biometric data and vital signs. We further explain a classification method for suspected COVID-19 infection based on the measured vital signs and symptoms. The results of this study can be applied in patient classification by mobile-based edge computing applications. The correlation between symptoms comprising cough, sore throat, fever, headache, myalgia, and arthralgia are analyzed in the model. We implement a machine learning classification model using vital signs for performance evaluation, and propose an ensemble model realized by fine-tuning the high-performing classification models. The proposed ensemble model successfully distinguishes suspected patients with an accuracy, area under curve, and F1 scores of 94.4%, 98.4%, and 94.4%, respectively.

Exploratory Field and Laboratory Investigation on the Use of Noncontact Digital Ski Sensor in the South Korea Expressway Network

In the case of asphalt pavement construction, better smoothing and reliable material performance acquisition are essential. In South Korea, the next-generation asphalt pavement-smoothing technology, known as the noncontact digital ski (NCDS), started to be used in expressway construction in 2018, making this system an essential tool in the paving industry. The present work thoroughly assessed how employing the NCDS system affected the response of the pavement material at low temperatures. Portions of paved roads with and without NCDS were assessed for the international roughness index (IRI, m/km). The development of thermal stress propagation was then examined using the bending beam rheometer on asphalt samples from the road. Based on straightforward visual and statistical analysis, it was discovered that using NCDS produces significantly lower IRI and reduced thermal stress, which raises the possibility that using NCDS has the potential for better low-temperatures predictions.

Non-Contact Adaptive Voltage Sensor Based on Electric Field Coupling Principle.

Non-contact voltage sensors based on the principle of electric field coupling have the advantages of simple loading and unloading, high construction safety, and the fact that they are not affected by line insulation. They can accurately measure line voltage without the need to connect to the measured object. Starting from the principle of non-contact voltage measurement, this article abstracts a non-contact voltage measurement model into the principle of capacitive voltage sharing and deduces its transfer relationship. Secondly, it is theoretically inferred that the edge effect of the traditional symmetric structure sensor plate will cause the actual capacitance value between the sensor plates to be greater than the theoretically calculated capacitance value, resulting in a certain measurement error. Therefore, the addition of an equipotential ring structure is proposed to eliminate the edge additional capacitance caused by the edge effect in order to design the sensor structure. In addition, due to the influence of sensor volume, material dielectric constant, and other factors, the capacitance value of the sensor itself is only at pF level, resulting in poor low-frequency performance and imbuing the sensor with a low voltage division ratio. In this regard, this article analyzes the measurement principle of non-contact voltage sensors. By paralleling ceramic capacitors between the two electrode plates of the sensor, the capacitance of the sensor itself is effectively increased, improving the low-frequency performance of the sensor while also increasing the sensor's voltage division ratio. In addition, by introducing a single pole double throw switch to switch parallel capacitors with different capacitance values, the sensor can have different voltage division ratios in different measurement scenarios, giving it a certain degree of adaptability. The final sensor prototype was made, and a high and low voltage experimental platform was built to test the sensor performance. The experimental results showed that the sensor has good linearity and high measurement accuracy, with a ratio error of within ±3%.

Research progress of multifunctional flexible proximity sensors

As a non-contact sensor, flexible proximity sensor can sense the proximity of target objects to achieve position recognition, obstacle avoidance, human-computer interaction and other functions. It has important application prospects in environmental detection, human health monitoring, robot electronic skin and other fields. In recent decades, a variety of flexible multifunctional sensors based on proximity sensing have emerged, and how to improve and optimize their performance has become a research hotspot. This review summarizes the classification, performance index and research progress of flexible proximity sensors with different sensing types. In particular, the design principle, structure composition, material selection and manufacturing process of the current flexible proximity sensors are discussed in detail. Then, the performance of proximity sensing, realizable functions and application scenarios are compared among the reviewed research results. Finally, we discuss the challenges faced by flexible proximity sensors, and summarize and prospect the research direction of flexible proximity sensors. This paper aims to provide important reference value for further improving and optimizing the performance of the flexible proximity sensor and developing the next generation of multifunctional wearable devices.

Iron Oxide-Based Nanoparticles for Fast-Response Humidity Sensing, Real-Time Respiration Monitoring, and Noncontact Sensing

Iron Oxide-Based Nanoparticles for Fast-Response Humidity Sensing, Real-Time Respiration Monitoring, and Noncontact Sensing

Signal processing and acoustic calibration method of millimeter-wave vibration sensor

Millimeter-wave sensors can be utilized as non-contact vibration sensors. Applications of millimeter-wave vibration sensors are the vital sensing of humans (heartbeat, respiration, body motion), factory machines, and vibration sensing of social infrastructures, such as buildings and bridges. Millimeter-wave vibration sensors can simultaneously detect the position and the waveforms of the vibration displacements of vibration objects. The primary signal processing of millimeter-wave sensors is two-dimensional fast Fourier transform (2D-FFT), detecting the arrival direction (DOA) and processing the micro-Doppler signals. The detectable areas of the millimeter-wave vibration sensors are defined using the parameters related to these three signal-processing blocks. Measured vibration waveforms by millimeter-wave vibration sensors include all components of the vibration displacements in the defined detectable area. Therefore, the waveform of the vibration displacement is influenced by the definition of the detectable area and the vibration form of the vibrating object. The measured values of millimeter-wave vibration sensors must be calibrated with attention to these influences. The vibration waveforms of vibrating objects are estimated by acoustic measuring methods, such as the laser Doppler vibrometer and the parallel-phase shifting interferometry. This paper describes calibration methods of millimeter-wave vibration sensors employing these two measuring methods.

Ratiometric optical temperature sensor with wide range and high sensitivity based on the emission of Dy3+ ion-doped Ca5(PO4)2SiO4 phosphor

There is an urgent demand for the development of non-contact optical temperature sensors that possess a wide temperature measurement range and high sensitivity, particularly for extreme environments. In this study, Dy3+-doped Ca5(PO4)2SiO4 phosphors were prepared and comprehensively analyzed. XRD, SEM, EDS, Raman spectrum, as well as excitation and emission spectrum were employed to investigate the structural, photoluminescent, and temperature-dependent properties of the phosphors. Under 349 nm excitation, the luminescence intensity ratio (LIR) of Dy3+ ions at 453 nm (4I15/2) and 480 nm (4F9/2) exhibited a strong correlation with temperature within the range of 296-1073 K. By fitting the FIR of I453 and I480 at different temperatures using Boltzmann equations, we observed a larger energy gap, indicating high relative sensitivity of the synthesized phosphor. Additionally, Ca4.95(PO4)2SiO4: 0.05Dy3+ phosphor shows excellent temperature repetitiveness. These findings highlight the potential applications of Ca5(PO4)2SiO4: Dy3+ phosphors as highly sensitive ratiometric optical temperature sensor over a wide temperature range.

Monitoring structural transformations in metamagnetic shape memory alloys by non-contact GMI technology

Different applications based on metamagnetic shape memory alloy (MSMA) require monitoring the evolution of the martensitic transformation (MT) to optimize the actuation mechanism. To avoid interaction with the active material, a non-contact technique would be ideal. Nevertheless, non-contact detection involves complex methods like diffraction, optical analysis, or electromagnetic technology. The present work demonstrates that the MT can be monitored without interaction with the active material using a low-cost technology based on the Giant Magnetoimpedance (GMI) effect. The GMI sensor is based on a (CoFe)SiB soft magnetic wire submitted to an alternating current and whose second harmonic voltage variation allows to detect changes in the strength of the stray magnetic fields linked to the metamagnetic phase transition. The sensor has been tested using the MT of a NiMnInCo MSMA. A specific application for environmental temperature control using the non-contact GMI sensor is proposed.

A Hybrid Strategy for Profile Measurement of Micro Gear Teeth.

A hybrid strategy is proposed to meet the challenge of obtaining the profile of micro gear teeth with a small modulus. Firstly, the contact probe segmentally obtained the falling flank profiles with an auxiliary lifting mechanism to avoid interference when it climbs on the rising slope. Then, the noncontact chromatic confocal displacement sensor efficiently acquired the gear peak positions to carry out the two-point error separation with the gear peak positions from the probe measurement. Finally, actual experiments were carried out to obtain the profile of a harmonic drive flexspline. Compared with the commercial ultraprecise profiler, the proposed method provides measurement results with a deviation of less than 20 μm. In conclusion, the hybrid strategy is feasible and accurate for drawing the micro gear teeth profile without any collision between the measuring probes and the measured workpiece.

A Noncontact Feed Microwave Metal Devices Deformation and Stress Sensor Based on Metamaterial

In this paper, a non-contact feed microwave metal deformation and stress sensor based on microwave harvesting metamaterial (MHMA) is proposed. It integrates HMA array, feed network and complementary cross finger split-ring resonator detector (CFSRRD). The sensor can be applied in the detection system composed of waveguide antenna (WA at 10GHz) and vector network analyzer (VNA). In processing of monitoring, the signal emitted by WA will be captured by MHMA array and output to CFSRRD through feed network. Then the response signal of CFSRRD will be returned to WA and analyzed by VNA. From analysis results, the deformation information of metal device will be obtained. Combined with the initial conditions of metal devices, the stress mutation information can be further obtained. Simulation and measurement results show that the designed sensor can detect the metal pipeline deformation caused by external force, pressure or high temperature with the reliable accuracy level of 500 μm (Submillimeter Level), and the minimum detectable radius of pipe is 30mm. It has the advantage of simple structure, strong adaptability and overcomes the shortcoming that traditional detection methods are difficult to detect the operating state of metal devices in complex environment.

Design and Development of a Variable Reluctance-Based Thin Planar Angle Sensor

In this paper, a new, thin non-contact angle sensor based on variable reluctance technique is presented. The proposed sensor has a disc-shaped eccentric rotor and a stator with two printed circuit boards with circular coils. These parts are easy to manufacture using established less expensive processes. The rotor and stator are positioned such that the inductances of the coils change as the angle changes. The inductance values are processed using a simple algorithm to obtain the sensing angle. For the stator, a dual coil structure is employed which ensures negligible sensitivity to the axial movement of the rotor. The sensor was designed with the help of finite element analysis. A prototype of the sensor has been built and tested. Static and dynamic performance tests were performed on the prototype. The resolution and worst-case linearity error of the prototype were found to be 0.06 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> and 0.7% respectively. The features and performance factors of the sensor are apt for industrial and automotive applications.

Vibrating capacitive electrostatic potential sensor based on a double cantilever tuning fork.

In this work, a vibrating capacitive sensor utilizing dual cantilever tuning fork resonance for electrostatic potential modulation was designed and fabricated. Initially, an electrostatic induction model was established, and the principle of non-contact electrostatic potential measurement was analyzed to identify the key factors influencing the sensor's performance. Subsequently, the vibration mode of the tuning fork was simulated to determine the mechanical dimensions of the tuning fork and the driving frequency of the piezoelectric crystal. Additionally, the concept of enhancing the uniformity of the electric field near the sensor by employing a shield plate was proposed. Simultaneously, the optimal mechanical parameters of the shielding plate were determined through multi-physical field simulation to improve the sensor's linearity. Finally, a compact calibration device was designed to measure the key performance parameters of the non-contact electrostatic potential sensor. The results demonstrate that the sensor has a measurement range of -10 to 10kV, a measurement accuracy better than ±3%, and a linearity of 0.46%. This work offers an alternative solution for non-contact potential measurement.