Hair Sensors Research Articles

Bidirectional biomimetic flow sensing with antiparallel and curved artificial hair sensors.

Background: Flow stimuli in the natural world are varied and contain a wide variety of directional information. Nature has developed morphological polarity and bidirectional arrangements for flow sensing to filter the incoming stimuli. Inspired by the neuromasts found in the lateral line of fish, we present a novel flow sensor design based on two curved cantilevers with bending orientation antiparallel to each other. Antiparallel cantilever pairs were designed, fabricated and compared to a single cantilever based hair sensor in terms of sensitivity to temperature changes and their response to changes in relative air flow direction.Results: In bidirectional air flow, antiparallel cantilever pairs exhibit an axially symmetrical sensitivity between 40 μV/(m s−1) for the lower air flow velocity range (between ±10–20 m s−1) and 80 μV/(m s−1) for a higher air flow velocity range (between ±20–32 m s−1). The antiparallel cantilever design improves directional sensitivity and provides a sinusoidal response to flow angle. In forward flow, the single sensor reaches its saturation limitation, flattening at 67% of the ideal sinusoidal curve which is earlier than the antiparallel cantilevers at 75%. The antiparallel artificial hair sensor better compensates for temperature changes than the single sensor.Conclusion: This work demonstrated the successive improvement of the bidirectional sensitivity, that is, improved temperature compensation, decreased noise generation and symmetrical response behaviour. In the antiparallel configuration, one of the two cantilevers always extends out into the free stream flow, remaining sensitive to directional flow and preserving a sensitivity to further flow stimuli.

A biomimetic multifunctional electronic hair sensor

A high performance electronic hair sensor with multiple functionalities is fabricated via fully mimicking the sensory hair cell structure of human skin.

Bat-inspired integrally actuated membrane wings with leading-edge sensing

This paper presents a numerical investigation on the closed-loop performance of a two-dimensional actuated membrane wing with fixed supports. The proposed concept mimics aerodynamic sensing and actuation mechanisms found in bat wings to achieve robust outdoor flight: firstly, variable membrane tension, which is obtained in bats through skeleton articulation, is introduced through a dielectric-elastomer construction; secondly, leading-edge airflow sensing is achieved with bioinspired hair-like sensors. Numerical results from a coupled aero-electromechanical model show that this configuration can allow for the tracking of prescribed lift coefficient signals in the presence of disturbances from atmospheric gusts. In particular, disturbance measurements through the hair sensor (a feedforward control strategy) are seen to provide substantial advantage with respect to a reactive (feedback) control strategy determining a reduction of the oscillations of the lift coefficient.

Geometric scaling of artificial hair sensors for flow measurement under different conditions

Artificial hair sensors (AHSs) have been developed for prediction of the local flow speed and aerodynamic force around an airfoil and subsequent application in vibration control of the airfoil. Usually, a specific sensor design is only sensitive to the flow speeds within its operating flow measurement region. This paper aims at expanding this flow measurement concept of using AHSs to different flow speed conditions by properly sizing the parameters of the sensors, including the dimensions of the artificial hair, capillary, and carbon nanotubes (CNTs) that make up the sensor design, based on a baseline sensor design and its working flow condition. In doing so, the glass fiber hair is modeled as a cantilever beam with an elastic foundation, subject to the distributed aerodynamic drag over the length of the hair. Hair length and diameter, capillary depth, and CNT height are scaled by keeping the maximum compressive strain of the CNTs constant for different sensors under different speed conditions. Numerical studies will demonstrate the feasibility of the geometric scaling methodology by designing AHSs for aircraft with different dimensions and flight conditions, starting from the same baseline sensor. Finally, the operating bandwidth of the scaled sensors are explored.

Biomimic Hairy Skin Tactile Sensor Based on Ferromagnetic Microwires.

We present a multifunctional tactile sensor inspired by human hairy skin structure, in which the sensitive hair sensor and the robust skin sensor are integrated into a single device via a pair of Co-based ferromagnetic microwire arrays in a very simple manner. The sensor possesses a self-tunable effective compliance with respect to the magnitude of the stimulus, allowing a wide range of loading force to be measured. The sensor also exhibits some amazing functions, such as air-flow detection, material property characterization, and excellent damage resistance. The novel sensing mechanism and structure provide a new strategy for designing multifunctional tactile sensors and show great potential applications on intelligent robot and sensing in harsh environments.

Aerodynamic parameters from distributed heterogeneous CNT hair sensors with a feedforward neural network

Distributed arrays of artificial hair sensors have bio-like sensing capabilities to obtain spatial and temporal surface flow information which is an important aspect of an effective fly-by-feel system. The spatiotemporal surface flow measurement enables further exploration of additional flow features such as flow stagnation, separation, and reattachment points. Due to their inherent robustness and fault tolerant capability, distributed arrays of hair sensors are well equipped to assess the aerodynamic and flow states in adverse conditions. In this paper, a local flow measurement from an array of artificial hair sensors in a wind tunnel experiment is used with a feedforward artificial neural network to predict aerodynamic parameters such as lift coefficient, moment coefficient, free-stream velocity, and angle of attack on an airfoil. We find the prediction error within 6% and 10% for lift and moment coefficients. The error for free-stream velocity and angle of attack were within 0.12 mph and 0.37 degrees. Knowledge of these parameters are key to finding the real time forces and moments which paves the way for effective control design to increase flight agility, stability, and maneuverability.

CNT‐Based Artificial Hair Sensors for Predictable Boundary Layer Air Flow Sensing

While numerous flow sensor architectures mimic the natural cilia of crickets, locusts, bats, and fish, the prediction of sensor output for given flow conditions based on the sensor properties has not been achieved. Challenges include difficulty in determining the electromechanical properties of the sensors, limited working knowledge of the boundary layer, low sensitivity to small hair deflections, and lack of models for large deflections. Within this work, hair sensors are fabricated using piezoresistive arrays of carbon nanotubes (CNTs) without traditional microelectromechanical processing. While correlating the CNT array electromechanical properties to synthesis conditions remains a challenge, a consistent, proportional, and predictable response to steady, boundary‐determined air flow is obtained using theory and measurement for various lengths of hairs. The moment sensitivity is shown to scale inversely with the CNT length and stiffness to a typical maximum of 1.3 ± 0.4% resistance change nN−1 m−1. The normalized CNT piezoresistivity is constant (1.1 ± 0.2) for a majority of the more than two dozen sensors examined despite the orders‐of‐magnitude variability in both sensitivity and CNT compressive modulus. The sensor sensitivity and noise both distinctly change as the flow transitions from steady and laminar to turbulent, suggesting the sensor may be capable of detecting flow transitions.

Aerodynamic Moment Model Calibration from Distributed Pressure Arrays

In recent years, studies on the role of distributed airflow mechanosensors in bird, bat, and insect flight behaviors have sparked a growing interest in integrating flow sensors, such as pressure or hair sensors, into flight control feedback systems of small unmanned aircraft. It is anticipated that a flight controller based on real-time distributed flow information feedback is more capable of rapidly responding to sudden airflow changes and may exhibit greater stability robustness properties than purely inertial feedback-based flight control laws. However, considering the uncertainty of state-of-the-art microflow sensor technologies, there is an urgent need for model calibration if flow information is to be used to calculate aerodynamic moments and/or forces for controlling aircraft motion. In this paper, a constrained least-squares estimator is developed to calculate the bias of distributed flow information to calibrate an aerodynamic moment model. Simulation and wind-tunnel experiment results demonstrate a significant improvement on the accuracy of the aerodynamic moment calculation after calibration.

A nano-microstructured artificial-hair-cell-type sensor based on topologically graded 3D carbon nanotube bundles

A design for a unique artificial-hair-cell-type sensor (AHCTS) based entirely on 3D-structured, vertically aligned carbon nanotube (CNT) bundles is introduced. Standard microfabrication techniques were used for the straightforward micro-nano integration of vertically aligned carbon nanotube arrays composed of low-layer multi-walled CNTs (two to six layers). The mechanical properties of the carbon nanotube bundles were intensively characterized with regard to various substrates and CNT morphology, e.g. bundle height. The CNT bundles display excellent flexibility and mechanical stability for lateral bending, showing high tear resistance. The integrated 3D CNT sensor can detect three-dimensional forces using the deflection or compression of a central CNT bundle which changes the contact resistance to the shorter neighboring bundles. The complete sensor system can be fabricated using a single chemical vapor deposition (CVD) process step. Moreover, sophisticated external contacts to the surroundings are not necessary for signal detection. No additional sensors or external bias for signal detection are required. This simplifies the miniaturization and the integration of these nanostructures for future microsystem set-ups. The new nanostructured sensor system exhibits an average sensitivity of 2100 ppm in the linear regime with the relative resistance change per micron (ppm μm−1) of the individual CNT bundle tip deflection. Furthermore, experiments have shown highly sensitive piezoresistive behavior with an electrical resistance decrease of up to ∼11% at 50 μm mechanical deflection. The detection sensitivity is as low as 1 μm of deflection, and thus highly comparable with the tactile hair sensors of insects, having typical thresholds on the order of 30–50 μm. The AHCTS can easily be adapted and applied as a flow, tactile or acceleration sensor as well as a vibration sensor. Potential applications of the latter might come up in artificial cochlear systems. In particular, the stable mechanical bending of the sensor up to 90° opens up unique application opportunities.

Bio-inspired directional sensor with piezoelectric microfiber and helical electrodes

Inspired by the hair cells of vertebrates and aquatics, we proposed a hair sensor design that mimics the directionality and linearity of hair cells. The sensor promotes a novel use of piezoelectric microfiber with unique helical electrodes. The sensing mechanism was modeled both analytically and numerically. The analytical model explicitly illustrates the effects of the various design parameters on the performance of the sensor; the numerical model took into account the complex geometry of the sensor and elucidated the importance of the orientation of piezoelectric polarization on the piezoelectric effects. Both models provide valuable insight to optimize the sensor performance. Hair sensor prototypes were fabricated and characterized in the laboratory. The sensor output was found to be linearly dependent on the magnitude of applied displacements. Besides, at the same magnitude of deflection, the sensor responses followed a cosine function with the loading direction, which is similar to what is observed on the directionality of biological hair cells. These experimental observations were consistent with the results of model simulations. An algorithm was proposed to determine the magnitude and direction of acoustic stimuli by utilizing just a pair of orthogonally polarized and closely spaced hair cell sensors.

Design and Analysis of a New Hair Sensor for Multi-Physical Signal Measurement.

A new hair sensor for multi-physical signal measurements, including acceleration, angular velocity and air flow, is presented in this paper. The entire structure consists of a hair post, a torsional frame and a resonant signal transducer. The hair post is utilized to sense and deliver the physical signals of the acceleration and the air flow rate. The physical signals are converted into frequency signals by the resonant transducer. The structure is optimized through finite element analysis. The simulation results demonstrate that the hair sensor has a frequency of 240 Hz in the first mode for the acceleration or the air flow sense, 3115 Hz in the third and fourth modes for the resonant conversion, and 3467 Hz in the fifth and sixth modes for the angular velocity transformation, respectively. All the above frequencies present in a reasonable modal distribution and are separated from interference modes. The input-output analysis of the new hair sensor demonstrates that the scale factor of the acceleration is 12.35 Hz/g, the scale factor of the angular velocity is 0.404 nm/deg/s and the sensitivity of the air flow is 1.075 Hz/(m/s)2, which verifies the multifunction sensitive characteristics of the hair sensor. Besides, the structural optimization of the hair post is used to improve the sensitivity of the air flow rate and the acceleration. The analysis results illustrate that the hollow circular hair post can increase the sensitivity of the air flow and the II-shape hair post can increase the sensitivity of the acceleration. Moreover, the thermal analysis confirms the scheme of the frequency difference for the resonant transducer can prominently eliminate the temperature influences on the measurement accuracy. The air flow analysis indicates that the surface area increase of hair post is significantly beneficial for the efficiency improvement of the signal transmission. In summary, the structure of the new hair sensor is proved to be feasible by comprehensive simulation and analysis.

Detection of flow separation and stagnation points using artificial hair sensors

Recent interest in fly-by-feel approaches for aircraft control has motivated the development of novel sensors for use in aerial systems. Artificial hair sensors (AHSs) are one type of device that promise to fill a unique niche in the sensory suite for aerial systems. In this work, we investigate the capability of an AHS based on structural glass fibers to directly identify flow stagnation and separation points on a cylindrical domain in a steady flow. The glass fibers are functionalized with a radially aligned carbon nanotube (CNT) forest and elicit a piezoresistive response as the CNT forest impinges on electrodes in a micropore when the hair is deflected due to viscous drag forces. Particle image velocimetry is used to measure the flow field allowing for the resulting moment and force acting on the hair to be correlated with the electrical response. It is demonstrated that the AHS provides estimates for the locations of both the stagnation and separation in steady flow. From this, a simulation of a heading estimation is presented to demonstrate a potential application for hair sensors. These results motivate the construction of large arrays of hair sensors for imaging and resolving flow structures in real time.

Design and fabrication of a metal core PVDF fiber for an air flow sensor

To track prey or avoid predators, many arthropods can detect variations in airflow and pressure gradients using an array of very thin and sensitive filiform hairs. In this study, metal core piezoelectric poly(vinylidene fluoride) (PVDF) fibers were prepared to mimic such hair sensors. The flexibility of the fibers was very good, which was helpful for overcoming the typical brittleness of piezoelectric ceramic fibers. At the same time, the diameter of the fibers was very small (down to 50 μm in diameter). In order to mimic the insects’ hairs to the maximum extent, which was expected to greatly improve the sensitivity of such PVDF fiber-based sensors, a feasible process to prepare and extract electrodes on the surface of the fibers had to be developed. Compared with stainless steel filament-core fibers, the molybdenum filament-core PVDF fibers were easy to stretch. The molybdenum filament was then covered by a cylindrical PVDF layer with a diameter of 400 μm. One half of the longitudinal surface of the fibers was spray-coated with a conductive silver adhesive. The metal core was then used as one electrode, and the conductive silver adhesive was used as the other electrode. After polarization, a single metal-core PVDF fiber could be used as an airflow sensor. The surface structure and the sections of the PVDF fiber were analyzed by scanning electron microscopy. The results of the mechanical stretching tests showed that the metal core greatly enhanced the mechanical properties of the PVDF fibers. X-ray diffraction revealed that the greater the stretching ratio, the higher the α-to-β-phase conversion rate during the preparation of the PVDF fibers. A single metal-core PVDF fiber was used as a bionic airflow sensor, and a mechanical model of this sensor was derived. The airflow sensing capability of the PVDF fiber was experimentally confirmed in a miniature wind tunnel. The results showed that a cantilevered metal-core PVDF fiber is capable of detecting the range and direction of the surrounding airflow variations. The experimental results also verified the theoretical model.

Characterization of bio-inspired hair flow sensors for oscillatory airflows: techniques to measure the response for both flow and pressure

Hair sensors for oscillatory airflow, operating in the regime of bulk flow, particle velocity or both, can be characterized by several methods. In this work, we discuss harmonic measurements on MEMS hair flow sensors. To characterize this type of flow sensor the use of three different types of oscillatory airflow source is investigated. A loudspeaker, a vibrating sphere and a standing wave tube all have specific characteristics regarding their acoustic field, frequency range, maximum velocity amplitude and the possibility to chose the ratio between pressure and flow velocity. They are compared and an overview is given with respect to which source is the most appropriate under specific conditions. Furthermore, by combining information from the flow setups used new insights into sensor operation can be gained.

Bioinspired Carbon Nanotube Fuzzy Fiber Hair Sensor for Air‐Flow Detection

Artificial hair sensors consisting of a piezoresistive carbon-nanotube-coated glass fiber embedded in a microcapillary are assembled and characterized. Individual sensors resemble a hair plug that may be integrated in a wide range of host materials. The sensors demonstrate an air-flow detection threshold of less than 1 m/s with a piezoresistive sensitivity of 1.3% per m/s air-flow change.

Estimation of squeeze film damping in artificial hair-sensor towards the detection-limit of crickets’ hairs

The filliform hairs of crickets are among the most sensitive flow sensing elements in nature. The high sensitivity of these hairs enables crickets in perceiving tiny air-movements which are only just distinguishable from noise. This forms our source of inspiration to design highly-sensitive array system made of artificial hair sensors for flow pattern observation i.e. flow camera. The realization of such high-sensitive hair sensor requires designs with low thermo-mechanical noise to match the detection-limit of crickets’ hairs. Here we investigate the damping factor in our artificial hair-sensor using different methods, as it is the source of the thermo-mechanical noise in MEMS structures. The theoretical analysis was verified with measurements in different conditions to estimate the damping factor. The results show that the damping factor of the artificial hair sensor as estimated in air is in the range of 10−12 N m/rad s−1, which translates into a 93 μm/s threshold airflow velocity.

Interfacing of differential-capacitive biomimetic hair flow-sensors for optimal sensitivity

Biologically inspired sensor-designs are investigated as a possible path to surpass the performance of more traditionally engineered designs. Inspired by crickets, artificial hair sensors have shown the ability to detect minute flow signals. This paper addresses developments in the design, fabrication, interfacing and characterization of biomimetic hair flow-sensors towards sensitive high-density arrays. Improvement of the electrode design of the hair sensors has resulted in a reduction of the smallest hair movements that can be measured. In comparison to the arrayed hairs-sensor design, the detection-limit was arguably improved at least twelve-fold, down to 1 mm s–1 airflow amplitude at 250 Hz as measured in a bandwidth of 3 kHz. The directivity pattern closely resembles a figure-of-eight. These sensitive hair-sensors open possibilities for high-resolution spatio-temporal flow pattern observations.

Emulating the directional sensitivity of fish hair cell sensor

This article describes the sensor development efforts that are inspired by the unique acoustic source tracking capability of aquatics such as fish. The physiological basis in the natural system has been attributed to the unique directional responses of hair cell sensor in the otolith. To emulate such directional transduction behaviors, a hair sensor based on piezoelectric microfiber is attempted. The sensor employs piezoelectric fiber both as the hair shaft and as the transduction element. A pair of electrodes was deposited on the fiber surface both for sensor signal collection and for polarizing the piezoelectric materials. Both computational modeling analysis and experimental study were conducted to validate the sensor performance. The hair sensor was found to possess directional responses that change in the pattern of a cosine function of the loading direction, resembling that observed in the hair cell sensor in the biological system. Such transduction behaviors pave the technical basis to emulate the unique acoustic tracking strategy by aquatics. PACS 07.07.Df, 07.10.Pz, 77.84.Cg, 87.19.lt

Towards a high-resolution flow camera using artificial hair sensor arrays for flow pattern observations

Flow-sensor arrays uncover the potential to measure spatio-temporal flow patterns rather than flow measurements at just a single point. We present in this paper the developments in design, fabrication and interfacing of biomimetic flow-sensor arrays, inspired by flow-sensitive organs (cerci) of crickets. For the purpose of high-resolution flow field visualization by our artificial hair flow-sensor arrays, various array-interfacing schemes are discussed and compared. Frequency division multiplexing (FDM) is shown to be an attractive method for efficient interrogation of capacitive array sensors. Using silicon-on-insulator technology with deep trench isolation structures, hair-based flow-sensors with differential capacitive read-out, arranged in single-chip arrays, have been successfully fabricated. FDM is implemented and used to interrogate individual hair sensors providing simultaneous real-time flow measurements from multiple hairs. This powerful approach is demonstrated by reconstruction of the field of a harmonic dipole field at the position of the hairs and by localizing this dipole source relative to the array elements.

Force sensitive carbon nanotube arrays for biologically inspired airflow sensing

The compressive electromechanical response of aligned carbon nanotube (CNT) arrays is evaluated for use as an artificial hair sensor (AHS) transduction element. CNT arrays with heights of 12, 75, and 225 µm are examined. The quasi-static and dynamic sensitivity to force, response time, and signal drift are examined within the range of applied stresses predicted by a mechanical model applicable to the conceptual CNT array-based AHS (0–1 kPa). Each array is highly sensitive to compressive loading, with a maximum observed gauge factor of 114. The arrays demonstrate a repeatable response to dynamic cycling after a break-in period of approximately 50 cycles. Utilizing a four-wire measurement electrode configuration, the change in contact resistance between the array and the electrodes is observed to dominate the electromechanical response of the arrays. The response time of the CNT arrays is of the order of 10 ms. When the arrays are subjected to constant stress, mechanical creep is observed that results in a signal drift that generally diminishes the responsiveness of the arrays, particularly at stress approaching 1 kPa. The results of this study serve as a preliminary proof of concept for utilizing CNT arrays as a transduction mechanism for a proposed artificial hair sensor. Such a low profile and light-weight flow sensor is expected to have application in a number of applications including navigation and state awareness of small air vehicles, similar in function to natural hair cell receptors utilized by insects and bats.