Search results

The measurement of aircraft barycenter is a verification of theoretical barycenter and is an important step of aircraft development. In the traditional measurement method of aircraft barycenter, the posture of the aircraft needs to be adjusted manually and is measured by optical instruments. The efficiency of posture adjustment depends on the proficiency of workers, and the accuracy of measurement is not high. In view of these problems of the current barycenter measurement method, this paper aims to propose an aircraft barycenter measurement method based on multi-posture.

In this method, the numerical control locator is used as a supporting part to fix and adjust the aircraft, and the calculation model of aircraft barycenter is established according to the principle of rigid body rotation and the principle of moment balance. Then, the influence of the main error sources on the measurement accuracy of aircraft barycenter is analyzed by Monte Carlo simulation, and the measurement accuracy is compared with that of the barycenter measurement method based on horizontal posture. Finally, the experiment platform of barycenter measurement was built in the laboratory and the experiments were carried out.

The experimental results show that the barycenter measurement method proposed in this paper has obvious advantages in measurement accuracy and efficiency compared with the traditional method.

This method can be used to measure the barycenter of different types of aircraft quickly and automatically.

In the context of fixed-wing aircraft wing assembly, there is a need for a rapid and precise measurement technique to determine the center distance between two double-hole components. This paper aims to propose an optical-based spatial point distance measurement technique using the spatial triangulation method. The purpose of this paper is to design a specialized measurement system, specifically a spherically mounted retroreflector nest (SMR nest), equipped with two laser displacement sensors and a rotary encoder as the core to achieve accurate distance measurements between the double holes.

To develop an efficient and accurate measurement system, the paper uses a combination of laser displacement sensors and a rotary encoder within the SMR nest. The system is designed, implemented and tested to meet the requirements of precise distance measurement. Software and hardware components have been developed and integrated for validation.

The optical-based distance measurement system achieves high precision at 0.04 mm and repeatability at 0.02 mm within a range of 412.084 mm to 1,590.591 mm. These results validate its suitability for efficient assembly processes, eliminating repetitive errors in aircraft wing assembly.

This paper proposes an optical-based spatial point distance measurement technique, as well as a unique design of a SMR nest and the introduction of two novel calibration techniques, all of which are validated by the developed software and hardware platform.

To make the single‐antenna attitude method more useful as a back‐up or fault diagnostic system than was targeted originally.

The enhancement incorporates information from the GPS satellite constellation and aircraft dynamic model. The visibility of GPS satellites affects the accuracy of the aircraft's volocity that is the main source of single‐antenna attitude. In addition, to use the aircraft dynamic model is natural because single‐antenna attitude is for exclusive use of aircraft. These are considered and implemented as a covariance matrix or process model of Kalman filters. The enhanced performances are verified by an aircraft nonlinear simulation.

The proposed method estimates more accurate volocity and unpiased single‐antenna attitude by using satellite constellation information and the aircraft dynamics. Moreover, the implemented system has a structure that combines other navigation sensors easily.

It would be more desirable to perform further researches; sensor integration, stability against wind disturbance, and aircraft model uncertainty, etc.

A useful attitude sensor for a back‐up attitude system at low cost on manned aircraft or a main attitude system on unmanned aircraft that are sensitive to the mass or size of payload.

This paper has been the first to promote the potential of single‐antenna attitude and with only information that can be easily obtained.

The purpose of the paper is to present an approach to detect and isolate the aircraft sensor and control surface/actuator failures affecting the mean of the Kalman filter innovation sequence.

The extended Kalman filter (EKF) is developed for nonlinear flight dynamic estimation of an F‐16 fighter and the effects of the sensor and control surface/actuator failures in the innovation sequence of the designed EKF are investigated. A robust Kalman filter (RKF) is very useful to isolate the control surface/actuator failures and sensor failures. The technique for control surface detection and identification is applied to an unstable multi‐input multi‐output model of a nonlinear AFTI/F‐16 fighter. The fighter is stabilized by means of a linear quadratic optimal controller. The control gain brings all the eigenvalues that are outside the unit circle, inside the unit circle. It also keeps the mechanical limits on the deflections of control surfaces. The fighter has nine state variables and six control inputs.

In the simulations, the longitudinal and lateral dynamics of an F‐16 aircraft dynamic model are considered, and the sensor and control surface/actuator failures are detected and isolated.

A real‐time detection of sensor and control surface/actuator failures affecting the mean of the innovation process applied to the linearized F‐16 fighter flight dynamic is examined and an effective approach to isolate the sensor and control surface/actuator failures is proposed. The nonlinear F‐16 model is linearized. Failures affecting the covariance of the innovation sequence is not considered in the paper.

An approach has been proposed to detect and isolate the aircraft sensor and control surface/actuator failures occurred in the aircraft control system. An extended Kalman filter has been developed for the nonlinear flight dynamic estimation of an F‐16 fighter. Failures in the sensors and control surfaces/actuators affect the characteristics of the innovation sequence of the EKF. The failures that affect the mean of the innovation sequence have been considered. When the EKF is used, the decision statistics changes regardless the fault is in the sensors or in the control surfaces/actuators, while a RKF is used, it is easy to distinguish the sensor and control surface/actuator faults.

Optical measurement sensors are increasingly available, often finding application in measurement and inspection of manufactured products. For example, theodolites and laser trackers are already used to calibrate jigs and tooling. Digital photogrammetry is used in dimensional inspection of assemblies such as aircraft wings. Such tasks demand high performance sensors with 2D and 3D capability, large working envelopes, high accuracy, low measurement latency and increased flexibility. The availability of sensors which meet and exceed such criteria is fuelling new possibilities in the manufacturing process itself. Fixed tooling may be eliminated and replaced by flexible fixturing under the control of embedded sensor systems. Sensor technology is reviewed and a novel application presented.

This paper aims to propose a novel approach, in which the reference data for the flow angles calibration are obtained by using measurements coming from an inertial navigation system and an air data sensor.

This is obtained by using the Kalman filter theory for the evaluation of the reference angle-of-attack and angle-of-sideslip.

The designed Kalman filter has been implemented in Matlab/Simulink and validated using flight data coming from two very different aircraft, the Piaggio Aerospace P1HH medium altitude long endurance unmanned aerial system and the Alenia-Aermacchi M346 Master™ transonic trainer. This paper illustrates some results where the filter satisfactory behaviour is verified by comparing the filter outputs with the data coming from high-accuracy nose-boom vanes.

The methodology aims to lower the calibration costs of the air data systems of an advanced aircraft.

The calibration of air-data systems for the evaluation of the flow angles is based on the availability of high-accuracy reference measurements of angle-of-attack and angle-of-sideslip. Typically, these are obtained by auxiliary sensors directly providing the reference angles (e.g. nose-boom vanes). The proposed methodology evaluates the reference angle-of-attack and angle-of-sideslip by analytically reconstructing them using calibrated airspeed measurements and inertial data.

The purpose of this study is to detect and reconstruct a fault in pitot probe and static ports, which are components of the air data system in commercial aircrafts, without false alarm and no need for pitot-static measurements. In this way, flight crew will be prevented from flying according to incorrect data and aircraft accidents that may occur will be prevented.

Real flight data collected from a local airline was used to design the relevant system. Correlation analysis was performed to select the data related to the airspeed and altitude. Fault detection and reconstruction were carried out by using adaptive neural fuzzy inference system and artificial neural networks, which are machine learning methods. MATLAB software was used for all the calculations.

No false alarm was detected when the fault test following the fault modeling was carried out at 0–2 s range by filtering the residual signal. When the fault was detected, fault reconstruction process was initiated so that system output could be achieved according to estimated sensor data.

The presented alternative analytical redundant airspeed and altitude calculation scheme could be used when the pitot-static system contains any fault condition.

Instead of using the methods based on hardware redundancy, the authors designed a new system within the scope of this study. Fault situations that may occur in pitot probes and static ports are modeled and different fault scenarios that can be encountered in all flight phases have been examined.

As part of the V.10 F programme financed by Service Technique de la Production Aeronautique (STPA), AEROSPATIALE and DASSAULT — BREGUET have joined forces to produce a single Falcon 10 wing entirely made of carbon fibre. This wing has just been sent from the AEROSPATIALE Company's Nantes factory to the Toulouse Aernautic Testing Centre. A second wing will also be built, but this time, by DASSAULT‐BREGUET Biarritz plant. The two wings will be used for static fatigue testing. The programme calls for another pair of wings, one to be made by each of the same firms. They will later be mounted to a Falcon 10 for flight testing.

The Embedded GPS/INS System (EGI) has been used more widely as central navigation equipment of aircraft. For certain cases needing high attitude accuracy, star sensor can be integrated with EGI to improve attitude performance. Since the filtering‐correction loop has already built in finished EGI product, centralized or federated Kalman filter is not applicable for integrating EGI with star sensor; it is a challenge to design multi‐sensor information fusion algorithm suitable for this situation. The purpose of this paper is to present a double‐layer fusion scheme and algorithms to meet the practical need of constructing integrated multi‐sensor navigation system by star sensor assisting finished EGI unit.

The alternate fusion algorithms for asynchronous measurements and the sequential fusion algorithms for synchronous measurements are presented. By combining alternate filtering and sequential filtering algorithms, a kind of double‐layer fusion algorithms for multi‐sensors is proposed and validated by semi‐physical test in this paper.

The double‐layer fusion algorithms represent a filtering strategy for multiple non‐identical parallel sensors to assist INS, while the independent estimation‐correction loop in EGI is still maintained. It has significant benefits in updating original navigation system by integrating new sensors.

The approach described in this paper can be used in designing similar multi‐sensor information fusion navigation system composed by EGI and various kinds of sensors, so as to improve the navigation performance.

Compared with conventional approach, in the situation that centralized and federated Kalman filter are not applicable, the double‐layer fusion scheme and algorithms give an external filtering strategy for measurements of finished EGI unit and star sensors.