In-Hover Quadrotor Rotor Degradation Monitoring Using Null-Space Excitation and Lock-In Detection

In-flight propulsion system diagnosis in multirotor unmanned aerial vehicles (UAVs) remains a challenging problem due to closed-loop control interactions, strong environmental disturbances, and common-mode effects that obscure rotor-specific anomalies. Conventional passive monitoring approaches based solely on electrical or mechanical measurements are often insufficient for reliable fault localization and for distinguishing global degradations from nominal operation. This paper proposes an active diagnostic framework that exploits low-amplitude sinusoidal excitation injected into the control null space during hover operation. By employing lock-in detection, rotor responses are selectively extracted at the excitation frequency, enabling the derivation of robust amplitude-based sensitivity indicators from rotational speed, current, and electrical power signals. A pairwise signed diagnostic metric is formulated to achieve reliable localization of asymmetric rotor faults. In addition, an absolute indicator referenced to a baseline condition is introduced to capture symmetric degradations affecting all rotors through the combined use of current- and power-based sensitivities. The proposed method is validated in a high-fidelity quadrotor simulation environment incorporating viscous-friction and thrust-coefficient degradation faults. Extensive Monte Carlo analyses demonstrate robust fault-detection and localization performance, including scenarios that are indistinguishable using conventional pairwise normalization techniques.

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Publication Details

Journal
Drones
Published
2026-05-21
DOI
https://doi.org/10.3390/drones10050395
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
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article

In-Hover Quadrotor Rotor Degradation Monitoring Using Null-Space Excitation and Lock-In Detection

I. Lovas
Drones
Machine Fault Diagnosis Techniques
article

In-Hover Quadrotor Rotor Degradation Monitoring Using Null-Space Excitation and Lock-In Detection

I. Lovas
article en

Abstract

In-flight propulsion system diagnosis in multirotor unmanned aerial vehicles (UAVs) remains a challenging problem due to closed-loop control interactions, strong environmental disturbances, and common-mode effects that obscure rotor-specific anomalies. Conventional passive monitoring approaches based solely on electrical or mechanical measurements are often insufficient for reliable fault localization and for distinguishing global degradations from nominal operation. This paper proposes an active diagnostic framework that exploits low-amplitude sinusoidal excitation injected into the control null space during hover operation. By employing lock-in detection, rotor responses are selectively extracted at the excitation frequency, enabling the derivation of robust amplitude-based sensitivity indicators from rotational speed, current, and electrical power signals. A pairwise signed diagnostic metric is formulated to achieve reliable localization of asymmetric rotor faults. In addition, an absolute indicator referenced to a baseline condition is introduced to capture symmetric degradations affecting all rotors through the combined use of current- and power-based sensitivities. The proposed method is validated in a high-fidelity quadrotor simulation environment incorporating viscous-friction and thrust-coefficient degradation faults. Extensive Monte Carlo analyses demonstrate robust fault-detection and localization performance, including scenarios that are indistinguishable using conventional pairwise normalization techniques.

DronesVol. 10(5)
Obuda University (HU)
Openalex Percentile: Top 7%
Machine Fault Diagnosis Techniques
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