Sensors and Actuators A-physical最新文献

In this paper, we experimentally investigate selective actuation of the first few higher-order modes of a micromachined silicon nitride circular membrane (micro drum), which is actuated by electromagnetic forces. A novel design of electrodes is proposed to enable selective actuation for portions of the membrane with the Lorentz force, which excites efficiently the higher-order modes. With different electrode configurations, we show that the (0, 1) mode, the degenerate (1, 1) modes, and the (2, 1) mode can be selectively activated or deactivated using the orthogonality between the actuation force and the mode shapes. A reduced-order model for the circular membrane is established and used to explain the results.

It is well-known that acoustic energy sources can be seen as a promising alternative energy resource by using acoustic energy harvester (AEH) which can transform sound energy into usable electrical power. However, the current AEHs have been restricted by their narrow bandwidths and low energy conversion efficiencies. In this study, a broadband and high efficient AEH is presented. The proposed AEH comprises an open-end sonic black hole (SBH) structure and an electrodynamic loudspeaker. The sound pressure is amplified through the open-end SBH structure, then the loudspeaker is used as electricity generator to convert acoustic energy into electric energy. The open-end SBH is a cylindrical tube with an array of regularly-spaced rigid-walled thin rings. The inner radii of the SBH rings are quadratically decreasing and the SBH effect can be obtained. The model for energy harvesting and sound absorption performance of the proposed AEH is then presented. Finally, the open-end SBH is fabricated by 3D printing apparatus. A prototype of the AEH is designed and tested by using an impedance tube. The energy conversion efficiency and absorption coefficient from calculation and experiment show a reasonable agreement. The proposed AEH can convert 11 % of total incident sound energy from 50 Hz to 800 Hz. The maximum energy conversion efficiency can achieve 65 % at 425 Hz under optimal resistance load. Furthermore, the broadband sound absorption can also be achieved by using the proposed AEH.

Dynamic gesture recognition, which utilizes flexible wearable sensors and deep learning, is invaluable for human–computer interaction. Nevertheless, the primary challenges persist are the rapid detection of intricate gestures and the accurate recognition of dynamic signals. In this study, we suggest utilizing a microfiber sensor to identify the variations in wrist skin and detect dynamic gesture. In order to tackle the issue of insufficient feature extraction in the detected signals, resulting in reduced accuracy in recognition, we introduce a network dubbed EMT-Net (improve multi-head attention transformer network). This network utilizes a transformer encoder to capture and represent the characteristics of dynamic gesture signal and uses a CNN to classify the encoded features. To ensure that the model comprehensively captures the temporal and statistical characteristics of the signals, we enhance the multi-head attention mechanism by restricting certain attention heads to concentrate solely on the statistical features of the signals while allowing others to focus on the temporal features and global dependencies. Furthermore, because of the varying discriminatory abilities of different characteristics, we have developed an attention module to redistribution the attention weights on statistical features. The experimental results demonstrate that the microfiber sensor effectively recognizes ten distinct forms of dynamic gesture signals. Simultaneously, EMT-Net attains proficient identification with an accuracy of 98.80%, precision of 98.81%, recall of 98.80%, and an F1 score of 98.80%. The application value of this dynamic gesture recognition technology, which utilizes microfiber sensors and EMT-Net, is significant. The forthcoming alterations in human–computer interaction, virtual reality, and various other domains are anticipated.

Defects on the surface and subsurface of the ferromagnetic steels can easily lead to structural failures. Eddy current testing is one of the most popular techniques for defect detection. In this paper, the direct current (DC) magnetization and a magnetic head-based eddy current array (MHECA) are integrated to propose the DCMHECA technique. This method can address the low testing efficiency of single probe testing and the channel multiplexing of array testing, and meanwhile detect deep surface and subsurface defects. The experimental results verify that the proposed DCMHECA can be used to locate rectangular and hole defects and quantify their depths with little channel interferences, which are indicated by low difference rates.

Advances in display technology have created the need for more efficient and natural multi-degree-of-freedom interaction devices. The movement of a single fingertip has six degrees of freedom (DOFs), but traditional rigid touchscreens usually sense only 2-D information. This article proposes a new deformable tactile interface, OneTip, for single-fingertip human-computer interaction with 6 DOFs. It is manufactured based on the principle of vision-based tactile sensing using virtual stereoscopic cameras, and its size is about twice that of a thumb. The contact surface of OneTip has a specially designed structure and material to mimic the sensitivity and softness of human skin. Also, OneTip employs a new sensing method to address the problem of soft fingertip pose estimation (measuring relative change only) with incipient slip effects. Experiments show that OneTip has good 6-D pose estimation accuracy, with root mean square errors (RMSE) of translation and rotation not exceeding 0.1 mm and 2.6°, respectively, within the linear interval (x and y: $-$1.2–1.2 mm; z: 0–3 mm; yaw: $-$15–15 deg; pitch and roll: $-$40–40 deg). Experiments were also conducted to explore the application of OneTip in typical virtual manipulation tasks and the possibility of combining it with other interaction devices.

The current work studies the impact of BaTiO₃ along with the various monosulfide on the sensing performance of a silver-coated surface plasmonic resonance sensor (SPR) for the noninvasive detection of glucose via urine samples. The considered monosulfides are GeS, ZnS, CdS, and CuS. After the optimization of the BaTiO₃ thickness to 13 nm over the silver based SPR sensor, all above mentioned monosulfides are investigated over the BaTiO₃ (BTO) layer individually. It is shown that GeS shows better performance compared to others. Maximum obtained sensitivity for the optimized structure (Prism (BK7)/ Ag (50 nm)/BaTiO₃ (13 nm)/GeS (01 Layer)/Urine sample) is 527 °/RIU (the highest ever reported to date) for urine sample refractive indices range 1.335, 1.336, 1.337, 1.338, and 1.341 for corresponding glucose concentration of 0 g/dl (non-diabetic), 0.625 g/dl (pre-diabetic), 1.25 g/dl (early diabetic), 2.5 g/dl (diabetic), and 5 g/dl (high-diabetic), respectively. The investigation produced a thorough picture of the distribution of electric fields for distinct monosulfide layers. Other investigated sensing performance parameters such as detection accuracy (DA), quality factor (QF), limit of detection (LOD) are also numerically calculated and are 0.227 deg⁻¹_, 97 RIU⁻¹ and 1.25e-5 respectively. The contrast of the suggested structure to similar relevant published work demonstrates its ability to be used as an efficient label-free biosensor.

A need exists for scalable, automated lab-on-chip systems to separate blood plasma for medical diagnostics. In this study, a vacuum-actuated peristaltic micropump (VPM) was developed, incorporating with the inertial microfluidic technique for the separation and collection of blood plasma from diluted blood. The features of the micropump were investigated by varying parameters such as frequency, vacuum pressure, and the number of microchannels. The highest achievable flow rate was found to be 832 µL/min. Subsequently, to minimize the occurrence of red blood cell rupture during the separation process and significantly reduce hemolysis, the configuration of the vertical wall inside the microchannel was modified to an inclined wall. This improvement was validated through experiments using high-speed cameras and fluorescent particles. Blood plasma separation was achieved with high efficiency (98.5 %), rapidity (<1 min), automation, and minimal whole blood usage (5 µL). Importantly, the vacuum actuator with an inclined wall obstruction design demonstrated very low hemolysis (less than 2 %).

Phosphor thermometry has demonstrated significant potential for nondestructive high-temperature measurements in gas turbines. To expand the measurement range through lifetime-based phosphor thermometry, we developed a novel phosphor, YAG:Dy co-doped with Tb (YAG:Dy,Tb). Three YAG:Dy,Tb samples with varying Tb concentrations were synthesized through the sol–gel method. A fiber-optic-coupled measurement system was established to capture multiple emission peaks of YAG co-doped with Dy³⁺ and Tb³⁺ at 544 nm, 484 nm, and 458 nm. Efficient energy transfer from Dy³⁺ to Tb³⁺ resulted in a substantial enhancement of Tb³⁺ emission at 544 nm under 355 nm excitation. Owing to the energy transfer, the temperature measurement range under the lifetime method was extended from room temperature to 1600 °C using the combination of Tb³⁺ emission at 544 nm and Dy³⁺ emission at 458 nm. YAG:Dy,Tb samples with higher concentrations of Tb³⁺ exhibited superior temperature measurement performance, mainly owing to their stronger signal-to-noise ratio at >1000 °C. The performances of different emission peaks were also compared according to temperature uncertainty, which generally ranged from 0.1 °C to 2.7 °C across the entire measurement range.

This paper presents the design and experimental evaluation of a silicon micro-machined resonant accelerometer featuring adjustable sensitivity. By integrating an electrostatic tuning module into the fundamental accelerometer structure, dynamic sensitivity adjustment becomes feasible, leveraging the softening effect of electrostatic negative stiffness to optimize range, noise, and bandwidth. Notably, the electrostatic tuning module integrates seamlessly with the core accelerometer structure, minimizing structural alterations. Through theoretical analysis and finite element simulation of the electrostatic negative stiffness principle, we have designed a novel accelerometer with adjustable sensitivity, which can enhance the sensitivity and reduces the bias-instability of the accelerometer with a relatively small adjustment voltage, without increasing structural complexity. The performance of the accelerometer was assessed through open-loop, closed-loop, and dynamic experiments, revealing that sensitivity increased from 843 Hz/g to 2611 Hz/g within a linear range of ±1 g when employing a sensitivity-enhancing bias voltage of 9 V. Moreover, the bias-instability is lowered down from 17.3 μg to 6.8 μg. This design offers a promising avenue for sensitivity tuning in MEMS resonant accelerometers.

Small variations in bolt component connection can have significant impacts on equipment operating safety and efficiency. A comprehensive understanding of the bolted status supports the equipment optimizing in in-situ health monitoring. Therefore, an improved bolt force measurement method is looking forward. Given the minimally invasive nature, potential for multi-parameter measuring, and ability to operate in harsh conditions, optic fiber sensors present an opportunity for equipment in-situ health monitoring. This paper first strengthened the confidence in embedding optic fiber force sensors within the bolts. Additionally, the FBG temperature self-compensation method is employed and successfully improved the force measurement accuracy, compared with the existing studies. The smart bolt configuration (addictively manufactured) refers to the standard bolt dimensions and integrates a metallized FBG optical fiber with a diameter of less than 0.5 mm. Then, the sensor performance was investigated through a series of routine mechanics tests and reports the force sensitivity of the designed smart bolt is 13.06 pm/kN (for M10 bolts) and 14.59 pm/kN (for M12 bolts), respectively. In dynamic force loading tests, the error of the sensor is within 4.95 %, and the maximum force detection error after temperature compensation is within 8.03 %, indicating an improved bolt force measuring accuracy. The anti-creep and anti-torque interference tests were undertaken to confirm the designed smart bolts are adequate for long-term service. The bolt vibration and connection test results have proved the mechanical solidity and reliability under extreme working conditions. This investigation confirms the viability of installing optic fiber force sensors in a bolt component. Confidence was established that the smart bolts have the advantages of compact structure, improved force detection accuracy, good reliability, and support for modern equipment in-situ health monitoring.