Multi-axis Sensor Research Articles

Development of a new soil–structure contact stress sensor for underground construction applications

This paper describes the design, development, calibration and validation of a novel soil–structure contact stress sensor. The new sensor design combines a novel operating principle, fibre Bragg grating (FBG) strain sensing and data-driven mapping techniques to create a multi-axis contact stress sensor that is both economical and suitably robust for deployment in underground construction applications. The instrumentation process is informed using a ‘virtual twin’ of the sensor in which synthetic data is generated by extracting and interpolating virtual FBG strains obtained from a large number of 3D finite-element calculations. A physical prototype is subsequently developed to demonstrate proof of concept. Results from laboratory validation tests give confidence in the sensor's ability to provide accurate contact stress measurements in typical soil–structure interface shear applications. In particular, the novel sensor structure and operating principle was shown to achieve excellent measurement of effective normal stress. The new sensor design harnesses many of the inherent benefits of FBGs including immunity to electromagnetic noise and water ingress, and the use a single lightweight cable and connector, which significantly simplifies installation on site compared to electrical multi-axis sensors.

Data Fusion for Displacement Estimation and Tracking of UAV Quadrotor in Dynamic Motion

The fusion of MIMU and GPS data is generally used to estimate the displacement and tracking of quadrotor UAVs. Meanwhile, displacement estimation inaccuracies during dynamic motion often occur. This error is caused by noise and limited sensor sampling rate especially occurs when the quadrotor changes its attitude rapidly to generate an instantaneous horizontal force. This paper proposes data fusion based on Kalman filter to estimate orientation and displacement. Experiments were also carried out to verify displacement accuracy, i.e. in single-axis and multi-axis sensor motions. The algorithm combines data from MIMU and GPS sensors so that acceleration data is filled in points where GPS data is not available. With this method, the predicted displacement from the MIMU sensor can be corrected every second with data from the GPS and produce accurate displacement and trajectory estimates.

Conformable and Compact Multiaxis Tactile Sensor for Human and Robotic Grasping via Anisotropic Waveguides

AbstractRich and accurate tactile perceptive capability is important for both humans and robots. Soft materials exhibit unique characteristics to construct high‐performance tactile sensors such as high sensitivity and high resistance to overload. In this work, a multiaxis tactile sensor based on a soft anisotropic waveguide that can distinguish normal force and shear force, which can greatly expand its potential uses in practice, is reported. First, the anisotropy of the waveguide sensor's response to vector forces is validated numerically and experimentally, and then two of those anisotropic units are embedded into one cladding with a crossed‐over layout, to form a multiaxis sensor. Then, a calibration algorithm is implemented on this sensor and the reconstruction of vector forces is achieved at an average accuracy of 28.0 mN for normal forces and 81.1 mN for shear forces, both with the sensing range of 1 N. Using this device, three demonstrations are shown to give outlooks of its potential application in human and robotic grasping tasks: a wearable tactile sensor for collecting human's haptic data during operation, a uniaxial gyroscope, and a robotic gripper's tactile sensor for assisting an unlocking task with a key. This work is a step toward more functional soft waveguide‐based force sensors.

Remote Health Monitoring of Wind Turbines Employing Vibroacoustic Transducers and Autoencoders

Implementation of remote monitoring technology for real wind turbine structures designed to detect potential sources of failure is described. An innovative multi-axis contactless acoustic sensor measuring acoustic intensity as well as previously known accelerometers were used for this purpose. Signal processing methods were proposed, including feature extraction and data analysis. Two strategies were examined: Mel Frequency Cepstral Coefficients pruned with principal component analysis and autoencoder-based feature extraction. The scientific experiment resulted in data gathering and analysis to predict potential wind turbine mechanism failures.

A wearable-HAR oriented sensory data generation method based on spatio-temporal reinforced conditional GANs

Human activity recognition based on wearable sensors plays an essential role in promoting many practical applications, such as healthcare, motion monitoring, medical examination, anomaly detection and human-computer interaction. It’s worth noting that longer temporal sensory sequences could reflect the characteristics of different daily activities more accurately. However, existing GANs-based time series generation methods could only synthesize uniaxial, multivariate or multidimensional sensor data over a relatively short span of time. These shorter synthetic time series could not effectively represent at least one complete daily activity cycle. To synthesize longer and more realistic multi-axial sensor data, this paper proposes a new customized GANs-based sensory data synthesizing method, which is dedicated to wearable activity recognition tasks, named Conditional SensoryGANs. Firstly, the elaborately designed MultiScale MultiDimensional (MSMD) spatiotemporal function module endows the proposed Conditional SensoryGANs with the capability of synthesizing longer sensory sequences, which could better characterize different behaviors with periodicity. Secondly, benefited from the well-designed Time-Frequency Enhancement (TFE) functional module, Conditional SensoryGANs could more accurately capture each axis’s spatiotemporal property and spatial correlation between different axes to improve the fidelity of synthetic sensor data. Thirdly, Conditional SensoryGANs could synthesize verisimilar wearable sensor data of the specified quantity and category under a unified framework with the embedded condition’s refined control. Qualitative visual evaluations demonstrate that the proposed method has more excellent capability for synthesizing verisimilar wearable multi-axial sensor data than the state-of-the-art GAN-based sensor data generation methods. Quantitative experiments also prove that it could achieve better results than off-the-shelf GANs-based time series methods for synthesizing wearable multi-axial sensor data. Meanwhile, empirical results demonstrate that synthetic sensor data from Conditional SensoryGANs can achieve comparatively approximate usability in the field of wearable human activity recognition than the real sensor data.

Carbon Black Sensor and Neural Network Model for Sensing Angle in Soft Pneumatic Actuators

Accurate control of soft robots is critical for positioning, locomotion, and manipulation applications. These soft systems, however, are currently limited by the lack of soft multi-axis sensor designs as well as a lack of models for interpreting complex soft sensor signals. In this work, we demonstrate a unique scheme for embedding soft carbon black strain sensors into a soft multi-axis pneumatic bellows actuator. In order to utilize the soft strain sensors for estimating orientation, the strain signals from each of the 12 sensors are compared against signals from a reference inertial measurement unit. Then, a time-based recurrent neural network is used to map the hysteretic soft sensor data to determine the yaw, pitch, and roll motions of the actuator. Results show that high accuracy estimates are achieved with average bias errors between 0 to 1.5 degrees and error standard deviations between 3 to 6 degrees. This novel application of soft multi-axis embedded sensors and neural network models demonstrates how fully soft actuators and sensors can be used to accurately determine robot orientation.

Design and performance evaluation of a multi-axis thin-film sensor for milling process measurement

A multi-axis sensor made of flexible, light, and sensitive PVDF (polyvinylidene fluoride) thin film is designed and fabricated for cutting force measurement in milling process. The single-layer PVDF thin film is constructed with six electrodes in a certain pattern, which has two electrodes in each pair to measure the signals due to bending moment as well as torque moment on the cutter in the process of milling. All the detected voltage signals will be calibrated by the digital signal processing unit and transmitted to the remote receiver via wireless communication. A cutting-force model is established in association with the measurement scheme that can compute the feed force, transverse force, and tangential force via the collected voltage signals from the electrodes. In experiment, the PVDF sensor is directly attached to the cutter, and the commercial dynamometer is implemented under the workpiece for synchronous measurement and comparison. As a result, the developed thin-film sensor associated with the sensing circuitry and wireless communication device as well as the cutting force model can effectively measure the important cutting force with satisfactory accuracy.

A wearable tool for continuous monitoring of movement disorders: clinical assessment and comparison with tremor scores.

The current gold standard for evaluating normal and impaired motor performances includes the use of the information provided by the patient and the Unified Parkinson's Disease Rating Scale (UPDRS). However, clinical rating scales are typically subjective and their time-limited duration may fail to capture daily fluctuations in motor symptoms resulting from Parkinson's disease. Recently, a new tool has been proposed for objective and continuous assessment of movement disorders based on the evaluation of frequential data content from multi-axial sensors and the identification of specific movement patterns typically associated with disorders. This reduces the probability of confusing physiological or pathological movements occurring at the same frequency with a different movement pattern. However, the data provided by the tool have not yet been compared with the information provided by the typically used clinical rating scales. The aim of this work is to investigate the possible relationship between UPRDS scores and the information provided by the tool for continuous and long-term monitoring. In this study, 20 patients with hand tremor were recruited. The UPDRS scoring was performed by a neurologist. Then, continuous monitoring was performed; data were acquired by means of the proposed wrist-worn-device "PD-Watch" for 24 h and then processed in order to get information and indexes on motor symptoms. Finally, these indexes were correlated to the UPDRS scores. Results show that the concise indexes provided by the tool correlate well with some items in UPDRS Part III, and this correlation has allowed to provide a more direct and immediate meaning to the values of the concise indexes detected by the tool. While results need to be extended with further studies, this can be considered useful information in the context of clinical trials and routine clinical practice for assessing motor symptoms and movement disorders.

Development and Application of Motor-Equipped Reaction Torque Sensor with Adjustable Measurement Range and Sensitivity

Various high-performance force/torque sensors have been developed for the purpose of advancing automation systems. However, the demand for simple torque measurement of rotating shafts continues to exist, and expensive multi-axis sensors need not be wasted here. In this paper we propose a simple motor-equipped single-axis reaction torque sensor to measure the applied torque continuously using a load cell. The proposed sensor has long lever and base linkages, and the adjustable moment arm consequently enables adjusting measurement range and sensitivity by repositioning the assembled load cell on the two linkages. This paper shows the design of the proposed torque sensor, and it is evaluated by experiments for various applied torque and lever length. Moreover, the sensor is applied to an existing example: a commercial balanced-arm lamp with and without its balancing spring. The proposed torque sensor can continuously and successfully measure the applied torque, and it will be utilized in various industries and laboratories without much money.

Design and Simulation Analysis of A Z Axis Microactuator with Low Mode Cross-Talk

ABSTRACTFor a vibration system, the best designed spring is compliant to a desired vibration mode while it is robust to other undesired modes. There are several types of spring design for displacing the proofmass along the x and y axes, however, very few designs of spring compliant to the z axis are introduced. Therefore, we propose a z axis microactuator in which the suspending spring is designed so that it is only compliant to vibration along the z axis. The suspending spring consists of straight beam stages mechanically coupled with each other via frames which are symmetrically designed around a center plate. The operation characteristics of the microactuator is investigated by theoretical expresses and numerical simulation. The frequency split between the z axis mode and undesired modes can obtain more than 45%. The operation frequency can be modified in a wide range, from 68 kHz to 400 kHz, by changing the dimensional parameters of spring beams. The spring beams can be lengthened to increase displacement in the z axis while the mode cross-talk is still suppressed. Compared to the previously reported researches, the current microactuator shows robustness to undesired vibration modes, which is potential for integration in low mode cross-talk multi-axis micro-stages and low-noise mechanical sensors.

Antirollover Experimental Method for a Liquid Tank Semitrailer

The liquid tank semitrailer has higher centroid and poor stability, and the vehicle is prone to rollover when turning or changing lanes at high speed. Thus, many companies have developed active antirollover systems in recent years. But the systems’ antirollover capabilities are different. However, there are no specific test conditions and test standards for antirollover systems. Taking this as a starting point, first, an automotive intelligent security cloud terminal and a multiaxis sensor are selected for the test data acquisition, and a remote data acquisition system based on a mobile signal is established. Second, a vehicle road test scheme with a free choice of route is designed. Set the rollover trigger conditions, obtain the test data through the database, and classify the data into dangerous scenarios. Third, the typical scenarios with rollover risk are obtained by data fitting. Finally, the typical antirollover system test conditions of the liquid tank semitrailer are obtained by optimizing and analysing the typical scenarios through the simulation software. The results show that the J-steering test with a turning radius of 45 m in both clockwise and counterclockwise directions can be used as an accurate typical test condition of the antirollover system of liquid tank semitrailers.

Attitude measurement method of spinning projectile based on infrared focal plane array

More and more attention has been paid to the infrared attitude measurement of missile because of its independence and anti-interference ability. In order to solve the problem that the installation error is easy to be introduced in the arrangement of conventional three-axis infrared sensors, the attitude measurement model of the infrared focal plane array is established based on the theory of missile-borne infrared attitude measurement. According to the established attitude measurement model of infrared focal plane array, the attitude calculation method of infrared focal plane array sensor is studied from the point of view of numerical value and low-pixel infrared image respectively. And the infrared focal plane array attitude measurement method based on numerical value and low-pixel image is proposed, which not only uses the way of single-axis infrared focal plane sensor array to avoid the installation error caused by the arrangement of multi-axis sensors, but also doesn’t use the method of integral summation in the calculation process to avoid the error accumulation. Finally, the attitude calculation method is verified by the semi-physical experiment, and the calculation errors of pitch angle and roll angle are respectively within ±1.5° and ±1°. The results of this study suggest that the proposed infrared focal plane array attitude measurement method based on numerical value and low-pixel image offers a new and promising approach.

Different Lower-Limb Setup Positions Do Not Consistently Change Backstroke Start Time to 10 m.

Backstroke starts involve the athlete starting from a flexed position with their feet against the pool wall and then extending their ankles, knees, hips and back to push off; however, swimmers can start in different positions. The purpose of this study was to evaluate the performance impact of different knee extension angles in the setup position for a backstroke start. Ten backstroke swimmers completed maximum-effort starts in each of two setup positions: one with the knees maximally flexed, and one with the knees less flexed. The start handles and touchpad were instrumented with multi-axial force sensors. Activity of major hip and knee extensors was measured using surface electromyography. Body position in the sagittal plane was recorded using high-speed cameras. There was no overall difference in time to 10 m between the two conditions (p = 0.36, dz = 0.12), but some participants showed differences as large as 0.12 s in time to 10 m between start conditions. We observed that starts performed from a setup position with less knee flexion had an average 0.07 m greater head entry distance (p = 0.07, dz = 0.53), while starts from a setup position with maximal knee flexion had an average 0.2 m/s greater takeoff velocity (p = 0.02, dz = 0.78). Both head entry distance and takeoff velocity are related to start performance, suggesting each position may optimize different aspects of the backstroke start. Coaches should assess athletes individually to determine which position is optimal.

Driving and detection system of vibrating piezoelectric gyroscope at atmospheric pressure for multi-axial inertia sensor

We developed a driving and sensing system for a multi-axial inertial sensor that operates at atmospheric pressure using vibrating piezoelectric gyroscope sensors. We developed driving circuit modules with self-oscillation and an automatic gain controller and a synchronous detection circuit for demodulation of the sensing signals. The self-oscillation function was tested using a charging amplifier and phase shifter. Self-oscillation works by detecting a displacement signal differentially, adjusting it by a phase of π/2, and sending it to the oscillation signal generator. The stop time was improved from 15 to 3 ms using an inverse driving module. The driving circuit maintained stable oscillation throughout operation of the gyroscope because the automatic gain controller was added to the self-oscillation loop. A velocity demodulation method was implemented for the sensor to demodulate the outputs of angular velocities; this is more beneficial for decoupled vibrating gyroscopes compared to displacement demodulation. The response under angular rate was 1°/s in the x- and y-directions, and the measurement sensitivity was 17.2 µV/(°/s). The measured Q of the fabricated piezoelectric gyroscope was maintained stably at 400–500 at normal pressure.

Theoretical research on multi-axis maglev low-frequency vibration sensor

Theoretical research on multi-axis maglev low-frequency vibration sensor

A novel device for continuous monitoring of tremor and other motor symptoms.

The clinical assessment of Parkinson's disease (PD) symptoms is typically performed with neurological examinations and simple motor tests. However, this only takes into account the severity of motor symptoms during the length of the recording and fails to capture variations in a patient's motor state, which change continuously during the day. Most of the current methods for long-term monitoring of extrapyramidal symptoms are based on the use of a wearable magneto-inertial device that evaluates the frequential content of signals in the range of movement disorders. However, the typical daily motor activities performed by patients may have a power spectrum into the same range of motor symptoms, and habitual activity may be indistinguishable from that due to movement disorders. In this work, we report a new device and method for the continuous and long-term monitoring of tremor due to PD and other movement disorders to reduce the probability of mistaking the discrimination between extrapyramidal symptoms and normal daily activity. The method is based on the evaluation of frequential data content from multi-axial sensors and on the identification of specific movement patterns that Parkinsonian and extrapyramidal symptoms are typically associated with. In this study, 16 patients with movement disorders were recruited. While results need to be extended with further studies and clinical trials, the proposed device appears promising and suitable for the use as part of clinical trials and routine clinical practice for supporting the evaluation of motor symptoms, disease progression, and the quantification of therapeutic effects.

A Multi-Axis Tactile Sensor Array for Touchscreen Applications

Touchscreens have been prevalent in daily life and ubiquitously applied in consuming electronics, industrial control systems, and other applications as human computer interfaces (HCIs), which offers a convenient way for the human to interact with the smart devices. However, the lack of tactile force feedback from these conventional touchscreens draws limitations on the dexterity and intuitiveness of those devices, which results in multi-level menus, waiting, multi-finger gestures, and so on. To enhance and diversify functions of touchscreens, this paper presents a multi-axis tactile sensor array prototype with a unique layered structure, which is capable of sensing both 3-directional tactile force and location information over an area of 60 mm $\times60$ mm by utilizing only $2\times2$ piezoresistive MEMS force sensors. This paper integrated the sensibility of tangential force and normal force within one system, which sheds light on multi-axis tactile applications and dramatically reduced the number of tactile cells. The sensor array design, fabrication and packaging, and test approaches have been discussed in this paper. Qualitative and quantitative analysis have been conducted to evaluate the performance of the tactile sensor array with tested force range of 0.1 ~ 0.5 N. The results demonstrated the functionality of proposed sensor array, which exhibited promising potential for touchscreen applications. [2017-0176]

Transient Characteristics of a Fluidic Device for Circulatory Jet Flow.

In this paper, we report on the design, simulation, and experimental analysis of a miniaturized device that can generate multiple circulated jet flows. The device is actuated by a lead zirconate titanate (PZT) diaphragm. The flows in the device were studied using three-dimensional transient numerical simulation with the programmable open source OpenFOAM and was comparable to the experimental result. Each flow is verified by two hotwires mounted at two positions inside each consisting chamber. The experiment confirmed that the flow was successfully created, and it demonstrated good agreement with the simulation. In addition, a prospective application of the device as an angular rate sensor is also demonstrated. The device is robust, is minimal in size, and can contribute to the development of multi-axis fluidic inertial sensors, fluidic amplifiers, gas mixing, coupling, and analysis.

Transverse sensitivity suppression using multi-axis surface encoder with parasitic error compensation

Transverse sensitivity that is mainly resulted from parasitic error motions can introduce undesired motion components and remarkably lower the manipulation qualities of most inertial sensors. This problem becomes even more apparent for multi-axial sensors as additional demands for multi-degree-of-freedom detection become higher. In this letter, a method to minify the transverse sensitivity of an inertial sensor by multi-degree-of-freedom optical sensing and measurement has been reported and tested. A multi-axis-surface-encoder-based biaxial optical accelerometer is fabricated for scheme validation. The surface encoder adopts multi-reading-unit arrangement, and it can not only detect small changes in displacement to calculate the applied acceleration along X- and Y-axes but also quantify the parasitic error motion caused by Z-twist. A suitable compensation strategy is also developed to reveal the concerned outputs without parasitic errors. Experimental results show that the configuration combined with the parasitic error compensation algorithm remarkably diminishes the sensor's transverse sensitivity and measurement error to 1.76% and 2.24%, respectively. Compared with the simple structure optimizations, the technique we proposed is more straightforward and effective. It is also applicable for transverse sensitivity suppression of other inertial sensors, allowing for a similar configuration, such as vibration sensors and inclinometers.

3D printing of multiaxial force sensors using carbon nanotube (CNT)/thermoplastic polyurethane (TPU) filaments

We developed a new method to directly fabricate 3D multiaxial force sensor using fused deposition modeling (FDM) 3D printing of functionalized nanocomposite filaments. Here, 3D cubic cross shaped force sensor is suggested to measure the forces from three axes (x, y and z). The sensor has two components – a structural part and a sensing part – both of which are concurrently fabricated by 3D printing with different functional filaments. The structural part is printed with thermoplastic polyurethane (TPU) filament and the sensing part is printed with carbon nanotube (CNT)/TPU nanocomposite filament with a piezoresistivity on the surface of the structural part. The resistances of the sensing part are measured in three axial directions; Rx, Ry, and Rz and the force applied on each axis is measured by the resistance change. The 3D-printed multiaxial force sensor could detect the sub-millimeter scale deflection and its corresponding force on each axis. According to the sensing principle, when Fz=4N was applied, Rz was decreased by 2% while only 0.2% resistance change of Ry was induced. In addition, a simultaneous resistance measurement system was developed for a real-time force sensing in three axes. With its customizability, rapid manufacturing, and economic feasibility, this manufacturing approach allows direct fabrication of multiaxial sensors without additional assembly or integration processes.