Aircraft flight parameter detection based on a neural network using multiple hot-film flow speed sensors

Fei, Haiping; Zhu, Rong; Zhou, Zhaoying; Wang, Jindong

doi:10.1088/0964-1726/16/4/035

Cited by 41 publications

(32 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A variety of different man-made sensors have also been used to measure the distribution of flow properties on the wings of small UAS. The most common are pressure sensors [6][7][8][9][10][11][12], but more novel sensors such as hotfilms [13,14] and artificial hair sensors [15,16] have also been used to measure flow velocity.…”

Section: Introductionmentioning

confidence: 99%

Distributed Pressure Sensing–Based Flight Control for Small Fixed-Wing Unmanned Aerial Systems

Wood

Araujo-Estrada

Richardson

et al. 2019

Journal of Aircraft

View full text Add to dashboard Cite

Small fixed-wing Unmanned Aerial Systems (UAS) might require increased agility when operating in turbulent wind fields. In these conditions, conventional sensor suites could be augmented with additional flow-sensing to extend the aircraft's usable flight envelope. Inspired by distributed sensor arrays in biological systems, a UAS with a chord-wise array of pressure sensors was developed. Wind-tunnel testing characterised these sensors alongside a conventional airspeed sensor and an angle-of-attack (AoA) vane, and showed a single pressure measurement gave a linear response to AoA pre-stall. Flight tests initially manually piloted the vehicle through pitching manoeuvres, then in a series of automated manoeuvres based on closed-loop feedback using an estimate of AoA from the single pressure port. The AoA estimate was successfully used to control the attitude of the aircraft. An Artificial Neural Network (ANN) was trained to estimate the AoA and airspeed using all pressure ports in the array, and validated using flight-trial data. The ANN more accurately estimated the AoA over a single port method with good robustness to stall and unsteady flow. Distributed flow sensors could be used to supplement conventional flight control systems, providing enhanced information about wing flow conditions with application to systems with highly flexible or morphing wings.

show abstract

Section: Introductionmentioning

confidence: 99%

Distributed Pressure Sensing–Based Flight Control for Small Fixed-Wing Unmanned Aerial Systems

Wood

Araujo-Estrada

Richardson

et al. 2019

Journal of Aircraft

View full text Add to dashboard Cite

show abstract

“…Often, air flow sensors are applied for velocity or wind speed estimation on UAVs [12,40]. Most of these flow sensors have in common that their one-dimensional measurement value z ∈ R depends on the air velocity v z along the fixed measurement axis of the sensor.…”

Section: Air Flow Sensor Modelmentioning

confidence: 99%

“…For example, Fei et al [12] and Tokutake et al [40] utilize thermal flow sensors on the wings of small unmanned aircrafts for the detection of flight parameters including the airspeed. For attitude estimation, Euston et al [11] fuse IMU and airspeed measurements of a UAV.…”

Section: Related Workmentioning

confidence: 99%

Efficient probabilistic localization for autonomous indoor airships using sonar, air flow, and IMU sensors

Müller

Burgard

2013

Advanced Robotics

View full text Add to dashboard Cite

In recent years, autonomous miniature airships have gained increased interest in the robotics community.Whereas their advantage lies in their abilities to move safely and to hover for extended periods of time, they at the same time are challenging as their payload is strictly limited and as their complex second-order kinematics makes the prediction of their pose and velocity through physical simulation difficult and imprecise. In this paper, we consider the problem of particle filter based online localization for a miniature blimp with lightweight ultrasound and air flow sensors as well as an IMU. We present probabilistic models dedicated to the special characteristics of the miniature and lightweight sensors applied on our blimp. Furthermore, we introduce an efficient odometry motion model based on the measurements of air flow sensors and an IMU which is less computationally demanding compared to the standard physical simulation-based control motion model. In experiments with a real blimp in a complex indoor environment, our approach has proven to allow accurate and reliable online localization of a miniature blimp and requires an order of magnitude fewer particles compared to the localization based on the standard control motion model. Furthermore, we demonstrate the substantial improvements in terms of localization accuracy when taking into account the temporal correlation of the air flow measurements in our novel odometry motion model.

show abstract

“…The readings of the sensors are acquired and converted into digital signals that are the inputs of the signal processor, whose outputs deduce the flight parameters based on micro controller2 processing. More details about hot-film flow speed sensors and the methodology to obtain flight parameters can be found in [13]. The micro controller2 on FPCM send the readings of flight speed, attack of angle, slip angle to autopilot through serial peripheral interface (SPI), and these sensor data are fused with other data like angular rate, acceleration, altitude, control commands, and etc.…”

Section: On-board Electronic Devicesmentioning

confidence: 99%

“…Air speed, the angle of attack and the slip angle are fundamental parameters in the control of aircraft, which are especially useful to identify wind direction and adapt the vehicle to the wind by positive control. Our previous work revealed that these flight parameters could be inferred from multiple hot-film flow speed sensors mounted on the surface of the wing [13].…”

Section: Introductionmentioning

confidence: 99%

A Novel Micro Air Vehicle with Flexible Wing Integrated with On-board Electronic Devices

Zhang

Zhu

Liu

et al. 2008

2008 IEEE Conference on Robotics, Automation and Mechatronics

Self Cite

View full text Add to dashboard Cite

This paper presents an electrically powered Micro Air Vehicle (MAV) with a flexible wing integrated with on-board electronic components that is built at Tsinghua University. The low aspect ratio wing, adopting the airfoil of S5010 and Zimmerman shape, is made up of a flexible printed circuit membrane (FPCM) that covers a thin carbon fiber skeleton. The real MAV prototype is tested in a low-speed wind tunnel in order to evaluate its aerodynamic characteristics. The comparing experiments are conducted on the flexible wing and its rigid counterpart with the same size and the same wing shape to illustrate the aerodynamic advantages of the flexible wing. The results of the wind tunnel experiments indicate that the flexible wing has a larger angle of stall, bigger maximum lift coefficient than the rigid one. However, the lift-drag ratio of the flexible wing varies in a complex way because the flexible wing also increases the drag with the lift growth. The FPCM functions as both the skin of the aircraft wing and the supporting substrate for the electronic components, such as micro hot-film flow speed sensors that are used to determine 3 fundamental flight parameters: air speed, angle of attack and sideslip angle. In addition, most of the signal processing circuits is distributed on the FPCM, which remarkably reduces the autopilot load. The dimensions of a homemade autopilot that is separately installed in the fuselage are 35x20xl2mm with the weight of 6g. Through experiments of real flights, the turning, climbing, maneuverability and wind resistant ability of the MAV are tested. The flight results show that the MAV can fly with good stability and maneuverability.

show abstract

Aircraft flight parameter detection based on a neural network using multiple hot-film flow speed sensors

Cited by 41 publications

References 11 publications

Distributed Pressure Sensing–Based Flight Control for Small Fixed-Wing Unmanned Aerial Systems

Distributed Pressure Sensing–Based Flight Control for Small Fixed-Wing Unmanned Aerial Systems

Efficient probabilistic localization for autonomous indoor airships using sonar, air flow, and IMU sensors

A Novel Micro Air Vehicle with Flexible Wing Integrated with On-board Electronic Devices

Contact Info

Product

Resources

About