Mechanical Sensors Research Articles

Essential Roles of PIEZO1 in Mammalian Cardiovascular System: From Development to Diseases.

Mechanical force is the basis of cardiovascular development, homeostasis, and diseases. The perception and response of mechanical force by the cardiovascular system are crucial. However, the molecular mechanisms mediating mechanotransduction in the cardiovascular system are not yet understood. PIEZO1, a novel transmembrane mechanosensitive cation channel known for its regulation of touch sensation, has been found to be widely expressed in the mammalian cardiovascular system. In this review, we elucidate the role and mechanism of PIEZO1 as a mechanical sensor in cardiovascular development, homeostasis, and disease processes, including embryo survival, angiogenesis, cardiac development repair, vascular inflammation, lymphangiogenesis, blood pressure regulation, cardiac hypertrophy, cardiac fibrosis, ventricular remodeling, and heart failure. We further summarize chemical molecules targeting PIEZO1 for potential translational applications. Finally, we address the controversies surrounding emergent concepts and challenges in future applications.

Online Handwriting Recognition Method with a Non-Inertial Reference Frame Based on the Measurement of Linear Accelerations and Differential Geometry: An Alternative to Quaternions.

This work describes a mathematical model for handwriting devices without a specific reference surface (SRS). The research was carried out on two hypotheses: the first considers possible circular segments that could be made during execution for the reconstruction of the trace, and the second is the combination of lines and circles. The proposed system has no flat reference surface, since the sensor is inside the pencil that describes the trace, not on the surface as in tablets or cell phones. An inertial sensor was used for the measurements, in this case, a commercial Micro-Electro Mechanical sensor of linear acceleration. The tracking device is an IMU sensor and a processing card that allows inertial measurements of the pen during on-the-fly tracing. It is essential to highlight that the system has a non-inertial reference frame. Comparing the two proposed models shows that it is possible to construct shapes from curved lines and that the patterns obtained are similar to what is recognized; this method provides an alternative to quaternion calculus for poorly specified orientation problems.

Research on the Measurement and Estimation Method of Wheel Resistance on a Soil Runway

In view of the fact that there is no suitable measurement method for tire driving resistance during the operation of a transporter on soil pavement, this paper proposes a simple measurement and estimation method for driving resistance on a soil runway based on the Bekker settlement model. In this paper, using the driving resistance equation based on the Bekker model, a simplified equation of driving resistance related to mass is proposed. Using the principle of kinematics, a simple test device for driving resistance was developed, and the test data of the test device were used to determine the parameters of the driving resistance estimation equation of the road surface. The driving resistance of the wheel running state was tested by the simulated aircraft load loading vehicle through the mechanical sensor, and the consistency between the theoretical value and the actual value of the driving resistance value under 8T, 10T, and 12T loads was verified. This research shows that the test method and estimation method have low cost and good accuracy and are suitable for wide promotion. The results of this paper provide a new idea and method for estimating the driving resistance of a wheel when a transporter runs on a soil road and also provide a reference for designing the length of a soil runway.

Damage-related imbalance identification for UAV composite propeller blades based on bidirectional temporal convolutional network and a flexible sensing system

Abstract Damage to the composite propeller blades could lead to rotational imbalance, which seriously affects the operational safety of unmanned aerial vehicles (UAVs), therefore, a novel method combining the Teager energy operator (TEO) and bidirectional temporal convolutional network (BiTCN) is proposed for detecting, localizing, and quantifying the damage-related imbalance in the blades. A flexible sensing system that contains Micro electro mechanical sensor accelerometers, signal conditioning, and wireless transmission is integrated with the composite propeller for in-situ signal acquisition of the propeller blades. TEO is applied to demodulate and enhance the pulse compositions in vibration signals and singular value decomposition (SVD) is employed to suppress random noise, resulting in denoised Teager energy spectrums for model input. Temporal convolutional network (TCN) has been widely used in sequence signal modeling because the causal dilated convolution could learn the context information of sequence signals while maintaining the advantages of parallel computing. To fully extract the signal features, BiTCN models are established to learn both the forward and backward signal features. Experimental verification results show that the proposed method detects the existence of imbalance with 100% accuracy, and the accuracies of localization and quantization are 99.65% and 98.61%, respectively, which are much higher than those of the models with the original signal as input. In addition, compared with the other four different algorithms, BiTCN is superior in terms of convergence speed and prediction accuracy.

Edge Computing and Fault Diagnosis of Rotating Machinery Based on MobileNet in Wireless Sensor Networks for Mechanical Vibration.

With the rapid development of the Industrial Internet of Things in rotating machinery, the amount of data sampled by mechanical vibration wireless sensor networks (MvWSNs) has increased significantly, straining bandwidth capacity. Concurrently, the safety requirements for rotating machinery have escalated, necessitating enhanced real-time data processing capabilities. Conventional methods, reliant on experiential approaches, have proven inefficient in meeting these evolving challenges. To this end, a fault detection method for rotating machinery based on mobileNet in MvWSNs is proposed to address these intractable issues. The small and light deep learning model is helpful to realize nearly real-time sensing and fault detection, lightening the communication pressure of MvWSNs. The well-trained deep learning is implanted on the MvWSNs sensor node, an edge computing platform developed via embedded STM32 microcontrollers (STMicroelectronics International NV, Geneva, Switzerland). Data acquisition, data processing, and data classification are all executed on the computing- and energy-constrained sensor node. The experimental results demonstrate that the proposed fault detection method can achieve about 0.99 for the DDS dataset and an accuracy of 0.98 in the MvWSNs sensor node. Furthermore, the final transmission data size is only 0.1% compared to the original data size. It is also a time-saving method that can be accomplished within 135 ms while the raw data will take about 1000 ms to transmit to the monitoring center when there are four sensor nodes in the network. Thus, the proposed edge computing method shows good application prospects in fault detection and control of rotating machinery with high time sensitivity.

Design of hexapod robot equipped with omnidirectional vision sensor for defect inspection of pipeline’s inner surface

Abstract Defect detection of inner surface of precision pipes is a crucial aspect of ensuring production safety. Currently, pipeline defect detection primarily relies on recording video for manual recognition, with urgent need to improve automation, quantification and accuracy. This paper presents a hexapod in-pipe robot with carrying capacity designed to transport the omnidirectional vision sensor to specified location within unreachable pipelines. The feasibility of the robot’s mechanical design and sensor load-carrying module is analyzed using theory calculations, motion simulations and finite element method. To address the challenges of small pixel ratio and weak background changes in panoramic images, a tiny defect segmentor (TDS) based on ResNet is proposed for detecting tiny defects on the inner surface of pipelines. The hardware and software systems are implemented, and the motion performance of the pipeline robot is validated through experiments. The results demonstrate that the robot achieves stable movement at a speed of over 0.1m/s and can adapt to pipe diameter ranging from of 110 to 130 mm. The novelty of the robot lies in providing stable control of the loaded vision sensor, with control precision of the rotation angle and the displacement recorded at 1.84% and 0.87%, respectively. Furthermore, the proposed method achieves a detection accuracy of 95.67% for tiny defects with a diameter less than 3 mm and provides defect location information. This pipeline robot serves as an essential reference for development of in-pipe 3D vision inspection system.

Dependability Assessment of a Dual-Axis Solar Tracking Prototype Using a Maintenance-Oriented Metric System

This study presents a numerical method for evaluating the maintainability of a dual-axis solar tracking system that can be deployed in residential areas for improved energy production. The purpose of this research manuscript is threefold. It targets the following objectives: (i) First, we present the construction of a self-sufficient dual-axis solar tracking system based on a low-power electronic schematic that requires only one motor driver to control the azimuth and elevation angles of the photovoltaic (PV) panel. The automated system’s main electronic equipment comprises 1 × Arduino Mega2560 microcontroller unit (MCU), 1 × TB6560 stepper driver module, 2 × stepper motors, 2 × relay modules, 1 × solar charge controller, 1 × accumulator, and 1 × voltage convertor. Additional hardware components such as photoresistors, mechanical limit switches, rotary encoders, voltage, and current sensors are also included to complete the automation cycle of the solar tracking system. (ii) Second, the Arduino Mega 2560 prototyping board is replaced by a custom-made and low-cost application-specific printed circuit board (ASPCB) based on the AVR controller. The MCU’s possible fault domain is then further defined by examining the risks of the poor manufacturing process, which can lead to stuck-at-0 (Sa0) and stuck-at-1 (Sa1) defects. Besides these issues, other challenges such as component modularity, installation accessibility, and hardware failures can affect the automated system’s serviceability. (iii) Third, we propose a novel set of maintenance-oriented metrics that combine the previously identified variables to provide a maintainability index (MI), which serves as a valuable tool for evaluating, optimizing, and maintaining complex systems such as solar tracking devices. The experimental data show that the computed MI improves the system’s maintainability and enhances repair operations, increasing uptime.

A stretchable and self-powered strain sensor with elastomeric electret

Stretchable deformation sensors play an important role in the perception and autonomy of soft robots. While various sensors have been reported, the mechanical sensor with self-powered capability and stretchability to suit extreme environment is urgently required. In this study, a stretchable, self-powered, sensitivity adjustable, and long-term stability strain sensor based on the stretchable electret is researched for deformation monitoring. This stretchable and self-powered sensor is composed of the dielectric elastomer with designed elastic modulus gradient and the stretchable electret with elastomeric and Nano-particles. The electro-mechanical capability of this designed sensor is researched and optimized by multi-objective optimization approach. The sensor exhibits self-powered capability, stretchability (tensile strain from 0% to 20%), tunable sensitivity (optimized from 5.7 to 5.9 pC mm−1), and stability, where electromechanical performance remains stable after 8000 stretching cycles. The feasibility of its autonomous sensing which promotes a wide range of potential application in soft robotics is demonstrated. This elastic modulus gradient-induced and net charge design significantly broadened the potential applications with large deformation and low-attached stiffness.

An adaptive gain phase‐locked loop for position sensorless control of permanent magnet synchronous motor drives

AbstractIn view of the cost and reliability issues caused by mechanical position sensors, position sensorless control (PSC) of permanent magnet synchronous motors (PMSMs) has received widespread attention. A series of rotor position estimation (RPE) schemes have been developed, in which the phase‐locked loop (PLL) plays an important role. However, the conventional phase‐locked loops face two thorny issues, one is the degradation of RPE performance under motor acceleration and deceleration conditions, and the other is high noise sensitivity. To this end, an adaptive gain PLL (AG‐PLL) is proposed for PSC of PMSM drives. The gains of the loop filter in the proposed AG‐PLL are adaptively adjusted with the estimation error in order to find a compromise between the estimation performance under motor acceleration and deceleration conditions and the noise sensitivity. Moreover, the proposed scheme avoids increasing the order of the PLL, so its dynamic performance is also guaranteed. The proposed scheme is tested based on the hardware‐in‐the‐loop platform.

Stretchable Piezoresistive Pressure Sensor Array with Sophisticated Sensitivity, Strain-Insensitivity, and Reproducibility.

This study delves into the development of a novel 10 by 10 sensor array featuring 100 pressure sensor pixels, achieving remarkable sensitivity up to 888.79kPa-1, through the innovative design of sensor structure. The critical challenge of strain sensitivity inherent is addressed in stretchable piezoresistive pressure sensors, a domain that has seen significant interest due to their potential for practical applications. This approach involves synthesizing and electrospinning polybutadiene-urethane (PBU), a reversible cross-linking polymer, subsequently coated with MXene nanosheets to create a conductive fabric. This fabrication technique strategically enhances sensor sensitivity by minimizing initial current values and incorporating semi-cylindrical electrodes with Ag nanowires (AgNWs) selectively coated for optimal conductivity. The application of a pre-strain method to electrode construction ensures strain immunity, preserving the sensor's electrical properties under expansion. The sensor array demonstrated remarkable sensitivity by consistently detecting even subtle airflow from an air gun in a wind sensing test, while a novel deep learning methodology significantly enhanced the long-term sensing accuracy of polymer-based stretchable mechanical sensors, marking a major advancement in sensor technology. This research presents a significant step forward in enhancing the reliability and performance of stretchable piezoresistive pressure sensors, offering a comprehensive solution to their current limitations.

A mechanical nano sensor based on magnetic-mediated sensitization for 5-HT detection

The real-time detection of neurotransmitters had attracted more attention due to the potential to provide vital information for pathology research, disease diagnosis, and clinical efficacy evaluation. Here, a magnetic-mediated nano sensor was developed to improve sensitivity for detection of serotonin (5-HT). The PDMS membrane doped with magnetic particles serves as a conversion element, enhancing the deformation of the thin film caused by surface stress under the action of a magnetic field and amplifying the resistance response signal of the nano sensor. The 5-HT detection associated with neurotransmitter diseases serve as a proof of concept revealing the magnetic sensitization. The detection limit of the 5-HT was decreased to 3.21 nM in the linear range of 5–500 nM, which was lower than that of the nano sensor without magnetic field. The clinical 5-HT samples were also been accurately detected, indicating a positive application potential of the as-prepared magnetic-mediated nano sensor. All these results reveal the high sensitivity and practicality of the as-prepared magnetic-mediated nano sensor and provide a new method for neurotransmitter diseases diagnosis.

Flexural rigidity of hawkmoth antennae depends on the bending direction

To probe its environment, the flying insect controllably flexes, twists, and maneuvers its antennae by coupling mechanical deformations with the sensory output. We question how the materials properties of insect antennae could influence their performance. A comparative study was conducted on four hawkmoth species: Manduca sexta, Ceratomia catalpae, Manduca quinquemaculata, and Xylophanes tersa. The morphology of the antennae of three hawkmoths that hover while feeding and one putatively non-nectar-feeding hawkmoth (Ceratomia catalpa) do not fundamentally differ, and all the antennae are comb-like (i.e., pectinate), markedly in males but weakly in females. Applying different weights to the free end of extracted cantilevered antennae, we discovered anisotropy in flexural rigidity when the antenna is forced to bend dorsally versus ventrally. The flexural rigidity of male antennae was less than that of females. Compared with the hawkmoths that hover while feeding, Ceratomia catalpae has almost two orders of magnitude lower flexural rigidity. Tensile tests showed that the stiffness of male and female antennae is almost the same. Therefore, the differences in flexural rigidity are explained by the distinct shapes of the antennal pectination. Like bristles in a comb, the pectinations provide extra rigidity to the antenna. We discuss the biological implications of these discoveries in relation to the flight habits of hawkmoths. Flexural anisotropy of antennae is expected in other groups of insects, but the targeted outcome may differ. Our work offers promising new applications of shaped fibers as mechanical sensors. Statement of significanceInsect antennae are blood-filled, segmented fibers with muscles in the two basal segments. The long terminal segment is muscle-free but can be flexed. Our comparative analysis of mechanical properties of hawkmoth antennae revealed a new feature: antenna resistance to bending depends on the bending direction. Our discovery replaces the conventional textbook scenario considering hawkmoth antennae as rigid rods. We showed that the pectinate antennae of hawkmoths behave as a comb in which the bristles resist bending when they come together. This anisotropy of flexural resistance offers a new mode of environmental sensing that has never been explored. The principles we found apply to other insects with non-axisymmetric antennae. Our work offers new applications for shaped fibers that could be designed to sense the flows.

Ultrasensitive Mechanical Sensor Using Tunable Ordered Array of Metallic and Insulating States in Vanadium Dioxide

Abstract Detecting tiny deformations or vibrations, particularly those associated with strains below 1%, is essential in various technological applications. Traditional intrinsic materials, including metals and semiconductors, face challenges in simultaneously achieving initial metallic state and strain-induced insulating state, hindering the development of highly sensitive mechanical sensors. Here we report an ultrasensitive mechanical sensor based on a strain-induced tunable ordered array of metallic and insulating states in the single-crystal bronze-phase vanadium dioxide [VO2(B)] quantum material. It is shown that the initial metallic state in the VO2(B) flake can be tuned to the insulating state by applying a weak uniaxial tensile strain. Such a unique property gives rise to a record-high gauge factor of above 607970, surpassing previous values by an order of magnitude, with excellent linearity and mechanical resilience as well as durability. As a proof-of-concept application, we use our proposed mechanical sensor to demonstrate precise sensing of the micro piece, gentle airflows and water droplets. We attribute the superior performance of the sensor to the strain-induced continuous metal-insulator transition in the single-crystal VO2(B) flake, evidenced by experimental and simulation results. Our findings highlight the potential of exploiting correlated quantum materials for next-generation ultrasensitive flexible mechanical sensors, addressing critical limitations in traditional materials.

Comparative Analysis of Point Cloud Similarity Based on 3D Surface Reconstruction Using Mechanical Depth Sensor

Comparative Analysis of Point Cloud Similarity Based on 3D Surface Reconstruction Using Mechanical Depth Sensor

Gramicidin A as a mechanical sensor for mixed nonideal lipid membranes.

Gramicidin A (gA) is a short hydrophobic β-helical peptide that forms cation-selective channels in lipid membranes in the course of transbilayer dimerization. The length of the gA helix is smaller than the thickness of a typical lipid monolayer. Consequently, elastic deformations of the membrane arise in the configurations of gA monomers, conducting dimer, and the intermediate state of coaxial pair, where gA monomers from opposing membrane monolayers are located one on top of the other. The gA channel is characterized by the average lifetime of the conducting state. The elastic properties of the membrane influence the average lifetime, thus making gA a convenient sensor of membrane elasticity. However, the utilization of gA to investigate the elastic properties of mixed membranes comprising two or more components frequently relies on the assumption of ideality, namely that the elastic parameters of mixed-lipid bilayers depend linearly on the concentrations of the components. Here, we developed a general approach that does not rely on the aforementioned assumption. Instead, we explicitly accounted for the possibility of inhomogeneous lateral distribution of all lipid components, as well as for membrane-mediated lateral interactions of gA monomers, dimer, coaxial pair, and minor lipid components. This approach enabled us to derive unknown elastic parameters of lipid monolayer from experimentally determined lifetimes of gA channel in mixed-lipid bilayers. A general algorithm was formulated that allows the unknown elastic parameters of a lipid monolayer to be obtained using gA as a mechanical sensor.

PCSK9 expression in fibrous cap possesses a marker for rupture in advanced plaque.

To date, PCSK9 inhibitors are well known for eliminating cardiac and cerebral artery ischemia events by lowering the serum lipid level. However, the pathophysiological value of in-plaque PCSK9 expression is still unclear. Advanced plaques removed by carotid endarterectomy were sectioned and stained to identify the PCSK9 expression pattern and its co-expression with rupture-relevant markers. To investigate the correlation of PCSK9 expression with regional blood shear flow, hemodynamic characteristics were analyzed using computational fluid dynamics, and representative parameters were compared between PCSK9 positive and negative staining plaques. To explore this phenomenon in vitro, human aortic vascular smooth muscle cells were used to overexpress and knock down PCSK9. The impacts of PCSK9 modulations on mechanical sensor activity were testified by western blot and immunofluorescence. Real-time polymerase chain reaction was used to evaluate the transcription levels of downstream rupture-prone effectors. PCSK9 distribution in plaque preferred cap and shoulder regions, residing predominantly in smooth muscle actin-positive cells. Cap PCSK9 expression correlated with fibrous cap thickness negatively and co-expressed with MMP-9, both pointing to the direction of plaque rupture. A hemodynamic profile indicated a rupture-prone feature of cap PCSK9 expression. In vitro, overexpression and knockdown of PCSK9 in human aortic vascular smooth muscle cells has positive modulation on mechanical sensor Yes-associated protein 1 (YAP) activity and transcription levels of its downstream rupture-prone effectors. Serial section staining verified in situ colocalization among PCSK9, YAP, and downstream effectors. Cap PCSK9 possesses a biomarker for rupture risk, and its modulation may lead to a novel biomechanical angle for plaque interventions.

Comparing the Mechanical Properties of Rice Cells and Protoplasts under PEG6000 Drought Stress Using Double Resonator Piezoelectric Cytometry.

Plant cells' ability to withstand abiotic stress is strongly linked to modifications in their mechanical characteristics. Nevertheless, the lack of a workable method for consistently tracking plant cells' mechanical properties severely restricts our comprehension of the mechanical alterations in plant cells under stress. In this study, we used the Double Resonator Piezoelectric Cytometry (DRPC) method to dynamically and non-invasively track changes in the surface stress (ΔS) generated and viscoelasticity (storage modulus G' and loss modulus G″) of protoplasts and suspension cells of rice under a drought stress of 5-25% PEG6000. The findings demonstrate that rice suspension cells and protoplasts react mechanically differently to 5-15% PEG6000 stress, implying distinct resistance mechanisms. However, neither of them can withstand 25% PEG6000 stress; they respond mechanically similarly to 25% PEG6000 stress. The results of DRPC are further corroborated by the morphological alterations of rice cells and protoplasts observed under an optical microscope. To sum up, the DRPC technique functions as a precise cellular mechanical sensor and offers novel research tools for the evaluation of plant cell adversity and differentiating between the mechanical reactions of cells and protoplasts under abiotic stress.

Flexible Mechanical Sensors Fabricated with Graphene Oxide-Coated Commercial Silk.

Many studies on flexible strain and pressure sensors have been reported due to growing interest in wearable devices for healthcare purposes. Here, we present flexible pressure and strain (motion) sensors prepared with only graphene oxide (GO) and commercial silk fabrics and yarns. The pressure sensors were fabricated by simply dipping the silk fabric into GO solution followed by applying a thermal treatment at 400 °C to obtain reduced GO (rGO). The pressure sensors were made from rGO-coated fabrics, which were stacked in three, five, and seven layers. A super-sensitivity of 2.58 × 103 kPa-1 at low pressure was observed in the seven-layer pressure sensor. The strain sensors were obtained from rGO-coated twisted silk yarns whose gauge factor was 0.307. Although this value is small or comparable to the values for other sensors, it is appropriate for motion sensing. The results of this study show a cost-effective and simple method for the fabrication of pressure and motion sensors with commercial silk and GO.

Effect of mechanical strain on lateral photovoltaic effect in n‐3C‐SiC/n‐Si hetorjunction Toward mechanical strain sensors capable of photoenergy harvesting

It is beneficial to have sensors capable of harvesting photoenergy in the era of Internet of Things (IoT) and 5 G integrated infrastructure. In this paper, we report the piezo-optoelectronic coupling characteristic of n-type 3C‐SiC/n‐type Si heterostructure and demonstrate it with a mechanical strain sensing device capable of harvesting photoenergy. The device is capable of generating a photovoltage as high as 3.4 mV when illuminated by a laser power as small as 10 μW, i.e. four times higher than similar sensors in previous studies. In addition, the strain sensitivity ΔV/V/ε ratios are 9.94 and 13.11 for tensile and compressive strain, respectively, which are five times better than conventional metal strain gauges. These findings contribute to the overall understanding of the piezo-optoelectronic coupling effect of SiC/Si heterojunction paving the way for the development of multifunctional sensors with light harvesting capabilities.

Reprogrammable, Recyclable Origami Robots Controlled by Magnetic Fields

Origami, the art of paper folding, has emerged as a versatile technique for crafting intricate 3D structures from 2D sheets. Combined with the magnetic actuation, origami paper becomes the building blocks for cost‐effective, wirelessly controllable magnetic robots. Herein, a biodegradable magnetic paper with excellent formability and recyclability is developed, facilitating its convenient utilization and disposal. The programable magnetic paper, fabricated with specific magnetization and crease patterns, enables the transformation of 2D sheets into predetermined 3D structures. Leveraging the lightweight and pliable nature of paper‐based materials, exceptional control of origami robots with fast response is demonstrated, enabling a wide range of locomotion. Furthermore, the paper‐based approach enables the incorporation of electronic functionality into magnetic actuators. By introducing conductive nanoparticles into magnetic paper, an electrically conductive substance is created. Constructing electronic circuits and integrating electronic components onto the paper‐based printed circuit board platform enables the repairing of broken circuits inside complicated equipment and optical sensing of surrounding environments in conjunction with locomotive robots. The origami robots have a huge potential to be facilitated in diverse fields with various functions, demonstrating complex locomotion, and integrating chemical, optical, thermal, and mechanical sensors for monitoring environmental conditions in hard‐to‐reach locations. The array of possibilities holds significant promise for the widespread application of these origami magnetic robots across a diverse spectrum of research fields in soft robotics.