A Framework for Diagnosis of Critical Faults in Unmanned Aerial Vehicles

Abstract

Unmanned Aerial Vehicles (UAVs) need a large degree of tolerance towards faults.If not diagnosed and handled in time, many types of faults can have catastrophic consequences if they occur during flight. Prognosis of faults is also valuable and so is the ability to distinguish the severity of the different faults in terms of both consequences and the frequency with which they appear. In this paper flight data from a fleet of UAVs is analysed with respect to certain faults and their frequency of appearance. Data is taken from a group of UAV's of the same type but with small differences in weight and handling due to different types of payloads and engines used. Categories of critical faults, that could and have caused UAV crashes are analysed and requirements to diagnosis are formulated. Faults in air system sensors and in control surfaces are given special attention. In a stochastic framework, and based on a large number of data logged during flights, diagnostic methods are employed to diagnose faults and the performance of these fault detectors are evaluated against flight data. The paper demonstrates a significant potential for reducing the risk of unplanned loss of remotely piloted vehicles used by the Danish Navy for target practice.

A Survey on Fault Diagnosis and Fault-Tolerant Control Methods for Unmanned Aerial Vehicles

“…In [73], a methodology that provides the ability to diagnose faults in control surfaces and air system sensors using data from a swarm of UAVs was discussed.…”

Detection and Isolation of Propeller Icing and Electric Propulsion System Faults in Fixed-Wing UAVs

“…This is because the mission planner has no guarantee of good weather [5,24]. The detection and diagnosis of several types of propulsion system faults in UAVs are well studied, e.g., [8][9][10][11][12]19]. However, detection of UAV propeller icing is a comparably neglected topic.…”

“…It is assumed that the measurements are noisy but bias-free. This is motivated by the reliable nature of sensors for angular speed and electric current, as well as the existence of methods that can detect and estimate faults on air speed sensors [19][20][21][22].…”

Safety control system technologies for UAVs: review and prospect

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