Sensor Review最新文献

Purpose

The purpose of this study is to introduce a new type of sensor which uses microwave metamaterials and direct-coupled split-ring resonators (DC-SRRs) to measure the dielectric properties of solid materials in real time. The sensor uses a transmission line with a bridge-type structure to measure the differential frequency, which can be used to calculate the dielectric constant of the material being tested. The study aims to establish an empirical relationship between the dielectric properties of the material and the frequency measurements obtained from the sensor.

Design/methodology/approach

In the proposed design, the opposite arm of the bridge transmission line is loaded by DC-SRRs, and the distance between DC-SRRs is optimized to minimize the mutual coupling between them. The DC-SRRs are loaded with the material under test (MUT) to perform differential permittivity sensing. When identical MUT is placed on both resonators, a single transmission zero (notch) is obtained, but non-identical MUTs exhibit two split notches. For the design of differential sensors and comparators based on symmetry disruption, frequency splitting is highly useful.

Findings

The proposed structure is demonstrated using electromagnetic simulation, and a prototype of the proposed sensor is fabricated and experimentally validated to prove the differential sensing principle. Here, the sensor is analyzed for sensitivity by using different MUTs with relative permittivity ranges from 1.006 to 10 and with a fixed dimension of 9 mm × 10 mm ×1.2 mm. It shows a very good average frequency deviation per unit change in permittivity of the MUTs, which is around 743 MHz, and it also exhibits a very high average relative sensitivity and quality factor of around 11.5% and 323, respectively.

Originality/value

The proposed sensor can be used for differential characterization of permittivity and also as a comparator to test the purity of solid dielectric samples. This sensor most importantly strengthens robustness to environmental conditions that cause cross-sensitivity or miscalibration. The accuracy of the measurement is enhanced as compared to conventional single- and double-notch metamaterial-based sensors.

Purpose

With the development of artificial intelligence, proximity sensors show their great potential in intelligent perception. This paper aims to propose a new planar capacitive sensor for the proximity sensing of a conductor.

Design/methodology/approach

Different from traditional structures, the proposed sensor is characterized by sawtooth-structured electrodes. A series of numerical simulations have been carried out to study the impact of different geometrical parameters such as the width of the main trunk, the width of the sawtooth and the number of sawtooths. In addition, the impact of the lateral offset of the approaching graphite block is investigated.

Findings

It is found that sensitivity is improved with the increase of the main trunk with, sawtooth width and sawtooth number while a larger lateral offset leads to a decrease in sensitivity. The performance of the proposed planar capacitive proximity sensor is also compared with two conventional planar capacitive sensors. The results show that the proposed planar capacitive sensor is obviously more sensitive than the two conventional planar capacitive sensors.

Originality/value

In this paper, a new planar capacitive sensor is proposed for the proximity sensing of a conductor. The results show that the capacitive sensor with the novel structure is obviously more sensitive than the traditional structures in the detection of the proximity conductor.

Purpose

Artificial fruit ripening is hazardous to mankind. In the recent past, artificial fruit ripening is increasing gradually due to its commercial benefits. To discriminate the type of fruit ripening involved at the vendors’ side, there is a great demand for on-sight ethylene detection in a nondestructive manner. Therefore, this study aims to deal with a comparison of various laboratory and portable methods developed so far with high-performance metrics to identify the ethylene detection at fruit ripening site.

Design/methodology/approach

This paper focuses on various types of technologies proposed up to date in ethylene detection, fabrication methods and signal conditioning circuits for ethylene detection in parts per million and parts per billion levels. The authors have already developed an infrared (IR) sensor to detect ethylene and also developed a lab-based setup belonging to the electrochemical sensing methods to detect ethylene for the fruit ripening application.

Findings

The authors have developed an electrochemical sensor based on multi-walled carbon nanotubes whose performance is relatively higher than the sensors that were previously reported in terms of material, sensitivity and selectivity. For identifying the best sensing technology for optimization of ethylene detection for fruit ripening discrimination process, authors have developed an IR-based ethylene sensor and also semiconducting metal-oxide ethylene sensor which are all compared with literature-based comparable parameters. This review paper mainly focuses on the potential possibilities for developing portable ethylene sensing devices for investigation applications.

Originality/value

The authors have elaborately discussed the new chemical and physical methods of ethylene detection and quantification from their own developed methods and also the key findings of the methods proposed by fellow researchers working on this field. The authors would like to declare that the extensive analysis carried out in this technical survey could be used for developing a cost-effective and high-performance portable ethylene sensing device for fruit ripening and discrimination applications.

Purpose

The performance of oil-filled pressure cores is very much affected by the corrugated diaphragm and the oil filling volume. The purpose of this paper is to show the effects of different corrugated diaphragms, different oil filling volumes and different treatments of the corrugated diaphragms on the performance of pressure sensors.

Design/methodology/approach

Pressure-sensitive cores with different diaphragm diameters, different diaphragm ripple numbers and different oil filling volumes are produced, and thermal cycling is introduced to improve the diaphragm performance, and finally the performance of each pressure-sensitive core is tested and the test data are analyzed and compared.

Findings

The experimental results show that the larger the diameter of the corrugated diaphragm used for encapsulation, the better the performance. For pressure-sensitive cores using smaller diameter corrugated diaphragms, the performance of one corrugation is better than that of two corrugations. When the number of corrugations and the diameter are the same size, the performance of the outer ring of the diaphragm with concave corrugations is better than that with convex corrugations. At the same time, the diaphragm after thermal cycling treatment and appropriate reduction of encapsulated oil filling can improve the performance of the pressure-sensitive core.

Originality/value

By exploring the effects of corrugated diaphragm and oil filling volume on the performance of oil-filled pressure cores, the design of oil-filled pressure sensors can be guided to improve sensor performance.

Purpose

In this study, an attempt has been made to collect the research that has been done on the construction and design of the H₂O₂ sensor. So far, many efforts have been made to quickly and sensitively determine H₂O₂ concentration based on different analytical principles. In this study, the importance of H₂O₂, its applications in various industries, especially the food industry, and the importance of measuring it with different techniques, especially portable sensors and on-site analysis, have been investigated and studied.

Design/methodology/approach

Hydrogen peroxide (H₂O₂) is a very simple molecule in nature, but due to its strong oxidizing and reducing properties, it has been widely used in the pharmaceutical, medical, environmental, mining, textile, paper, food production and chemical industries. Sensitive, rapid and continuous detection of H₂O₂ is of great importance in many systems for product quality control, health care, medical diagnostics, food safety and environmental protection.

Findings

Various methods have been developed and applied for the analysis of H₂O₂, such as fluorescence, colorimetry and electrochemistry, among them, the electrochemical technique due to its advantages in simple instrumentation, easy miniaturization, sensitivity and selectivity.

Originality/value

Monitoring the H₂O₂ concentration level is of practical importance for academic and industrial purposes. Edible oils are prone to oxidation during processing and storage, which may adversely affect oil quality and human health. Determination of peroxide value (PV) of edible oils is essential because PV is one of the most common quality parameters for monitoring lipid oxidation and oil quality control. The development of cheap, simple, fast, sensitive and selective H₂O₂ sensors is essential.

Purpose

The purpose of this study is to explore the use of smartphone-embedded microelectro-mechanical sensors (MEMS) for accurately estimating rotating machinery speed, crucial for various condition monitoring tasks. Rotating machinery (RM) serves a crucial role in diverse applications, necessitating accurate speed estimation essential for condition monitoring (CM) tasks such as vibration analysis, efficiency evaluation and predictive assessment.

Design/methodology/approach

This research explores the utilization of MEMS embedded in smartphones to economically estimate RM speed. A series of experiments were conducted across three test setups, comparing smartphone-based speed estimation to traditional methods. Rigorous testing spanned various dimensions, including scenarios of limited data availability, diverse speed applications and different smartphone placements on RM surfaces.

Findings

The methodology demonstrated exceptional performance across low and high-speed contexts. Smartphones-MEMS accurately estimated speed regardless of their placement on surfaces like metal and fiber, presenting promising outcomes with a mere 6 RPM maximum error. Statistical analysis, using a two-sample t-test, compared smartphone-derived speed outcomes with those from a tachometer and high-quality (HQ) data acquisition system.

Research limitations/implications

The research limitations include the need for further investigation into smartphone sensor calibration and accuracy in extremely high-speed scenarios. Future research could focus on refining these aspects.

Social implications

The societal impact is substantial, offering cost-effective CM across various industries and encouraging further exploration of MEMS-based vibration monitoring.

Originality/value

This research showcases an innovative approach using smartphone-embedded MEMS for RM speed estimation. The study’s multidimensional testing highlights its originality in addressing scenarios with limited data and varied speed applications.

Purpose

This paper aims to investigate the efficacy of teeth flux sensors in detecting, locating and assessing the severity of short-circuit faults in the stator windings of induction machines.

Design/methodology/approach

The experimental study involves inducing short-circuit winding turn variations on the induction machine’s stator and continuously measuring the RMS values across teeth flux sensors. Two crucial steps are taken for machine diagnosis: measurements under load operating conditions for fault detection and measurements under no-load conditions to determine fault location and severity.

Findings

The experimental results demonstrate that the proposed approach using teeth flux sensors is reliable and effective in detecting, locating and evaluating the severity of stator winding faults.

Research limitations/implications

While this study focuses on short-circuit faults, future research could explore other fault types and alternative sensor configurations to enhance the comprehensiveness of fault diagnosis.

Practical implications

The methodology outlined in this paper holds the potential to significantly reduce maintenance time and costs for induction machines, leading to substantial savings for companies.

Originality/value

This research contributes to the field by presenting an innovative approach that uses teeth flux sensors for a comprehensive fault diagnosis in induction machines. The originality lies in the effectiveness of this approach in providing reliable fault detection, location and severity evaluation.

Purpose

This study aims to investigate the potential of the decorated boron nitride nanocage (BNNc) with transition metals for capturing carbon monoxide (CO) as a toxic gas in the air.

Design/methodology/approach

BNNc was modeled in the presence of doping atoms of titanium (Ti), vanadium (V), chromium (Cr), cobalt (Co), copper (Cu) and zinc (Zn) which can increase the gas sensing ability of BNNc. In this research, the calculations have been accomplished by CAM–B3LYP–D3/EPR–3, LANL2DZ level of theory. The trapping of CO molecules by (Ti, V, Cr, Co, Cu, Zn)–BNNc has been successfully incorporated because of binding formation consisting of C → Ti, C → V, C → Cr, C → Co, C → Cu, C → Zn.

Findings

Nuclear quadrupole resonance data has indicated that Cu-doped or Co-doped on pristine BNNc has high fluctuations between Bader charge versus electric potential, which can be appropriate options with the highest tendency for electron accepting in the gas adsorption process. Furthermore, nuclear magnetic resonance spectroscopy has explored that the yield of electron accepting for doping atoms on the (Ti, V, Cr, Co, Cu, Zn)–BNNc in CO molecules adsorption can be ordered as follows: Cu > Co >> Cr > Zn ˜ V> Ti that exhibits the strength of the covalent bond between Ti, V, Cr, Co, Cu, Zn and CO. In fact, the adsorption of CO gas molecules can introduce spin polarization on the (Ti, V, Cr, Co, Cu, Zn)–BNNc which specifies that these surfaces may be used as magnetic-scavenging surface as a gas detector. Gibbs free energy based on IR spectroscopy for adsorption of CO molecules adsorption on the (Ti, V, Cr, Co, Cu, Zn)–BNNc have exhibited that for a given number of carbon donor sites in CO, the stabilities of complexes owing to doping atoms of Ti, V, Cr, Co, Cu, Zn can be considered as: CO →Cu–BNNc >> CO → Co–BNNc > CO → Cr–BNNc > CO → V–BNNc > CO → Zn–BNNc > CO → Ti–BNNc.

Originality/value

This study by using materials modeling approaches and decorating of nanomaterials with transition metals is supposed to introduce new efficient nanosensors in applications for selective sensing of carbon monoxide.

Purpose

Gesture recognition plays an important role in many fields such as human–computer interaction, medical rehabilitation, virtual and augmented reality. Gesture recognition using wearable devices is a common and effective recognition method. This study aims to combine the inverse magnetostrictive effect and tunneling magnetoresistance effect and proposes a novel wearable sensing glove applied in the field of gesture recognition.

Design/methodology/approach

A magnetostrictive sensing glove with function of gesture recognition is proposed based on Fe-Ni alloy, tunneling magnetoresistive elements, Agilus30 base and square permanent magnets. The sensing glove consists of five sensing units to measure the bending angle of each finger joint. The optimal structure of the sensing units is determined through experimentation and simulation. The output voltage model of the sensing units is established, and the output characteristics of the sensing units are tested by the experimental platform. Fifteen gestures are selected for recognition, and the corresponding output voltages are collected to construct the data set and the data is processed using Back Propagation Neural Network.

Findings

The sensing units can detect the change in the bending angle of finger joints from 0 to 105 degrees and a maximum error of 4.69% between the experimental and theoretical values. The average recognition accuracy of Back Propagation Neural Network is 97.53% for 15 gestures.

Research limitations/implications

The sensing glove can only recognize static gestures at present, and further research is still needed to recognize dynamic gestures.

Practical implications

A new approach to gesture recognition using wearable devices.

Social implications

This study has a broad application prospect in the field of human–computer interaction.

Originality/value

The sensing glove can collect voltage signals under different gestures to realize the recognition of different gestures with good repeatability, which has a broad application prospect in the field of human–computer interaction.