Investigation of Frequency-Domain-Based Vibration Signal Analysis for UAV Unbalance Fault Classification

Al-Haddad, Luttfi; Jaber, Alaa Abdulhady; Neranon, Paramin; Al-Haddad, Sinan

doi:10.30684/etj.2023.137412.1348

Cited by 15 publications

(6 citation statements)

References 20 publications

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“…Spectrum analysis based on FFT [40] was utilized to discriminate between the operational frequencies on a trimotor [41]. The states of healthy and damaged blade of a quadcopter are studied based on signal processing in real-time decisionmaking process [42]. However, sophisticated techniques such as Continuous Wavelet Transform (CWT) [43,44] and Discrete Wavelet Transform (DWT) [45][46][47][48]…”

Section: Fault Diagnosis Strategies For Predictive Maintenance Ismentioning

confidence: 99%

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Vibration Signal Processing for Multirotor UAVs Fault Diagnosis: Filtering or Multiresolution Analysis?

Al-Haddad,

Giernacki,

Shandookh

et al. 2023

Eksploatacja i Niezawodność – Maintenance and Reliability

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In the modern technological advancements, Unmanned Aerial Vehicles (UAVs) have emerged across diverse applications. As UAVs evolve, fault diagnosis witnessed great advancements, with signal processing methodologies taking center stage. This paper presents an assessment of vibration-based signal processing techniques, focusing on Kalman filtering (KF) and Discrete Wavelet Transform (DWT) multiresolution analysis. Experimental evaluation of healthy and faulty states in a quadcopter, using an accelerometer, are presented. The determination of the 1024 Hz sampling frequency is facilitated through finite element analysis of 20 mode shapes. KF exhibits commendable performance, successfully segregating faulty and healthy peaks within an acceptable range. While the six-level multi-decomposition unveils good explanations for fluctuations eluding KF. Ultimately, both KF and DWT showcase high-performance capabilities in fault diagnosis. However, DWT shows superior assessment precision, uncovering intricate details and facilitating a holistic understanding of fault-related characteristics.

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Section: Fault Diagnosis Strategies For Predictive Maintenance Ismentioning

confidence: 99%

“…Where 𝑡 represents time, 𝑤 is the radian frequency, and 𝑥(𝑤) is the signal transformed. In addition to that, it should be noted that frequency-domain-based analysis is heavily utilized in vibration analysis [54], especially those vibration signals acquired from quadcopter drones for the outcome of fault diagnosis [42].…”

Section: Levelsmentioning

confidence: 99%

Vibration Signal Processing for Multirotor UAVs Fault Diagnosis: Filtering or Multiresolution Analysis?

Al-Haddad,

Giernacki,

Shandookh

et al. 2023

Eksploatacja i Niezawodność – Maintenance and Reliability

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“…This distance is squared, yielding. |𝑥𝑥 − 𝑦𝑦| 2 . The presence of the negative sign in front of gamma (-g) implies that the resulting value will decrease exponentially as the distance between x and y increases.…”

Section: Machine Learning Models 31 Support Vector Machinementioning

confidence: 99%

“…The field of aeronautics consistently aims for innovation and progress to enhance the safety, effectiveness, and overall performance of aircraft Al-Haddadet al [1], Al-Haddadet al, [2]. Comprehending how tension is distributed across a model during wind tunnel tests holds significant importance for aircraft design and operations Cui et al [3], Westin et al, [4].…”

Section: Introductionmentioning

confidence: 99%

Enhancing Wind Tunnel Computational Simulations of Finite Element Analysis Using Machine Learning-Based Algorithms

Al-Haddad,

Jaber,

Ibraheem

et al. 2023

ETJ

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“…While recent research in advanced UAV technologies mainly focuses on fault diagnosis [4][5][6][7][8][9][10][11], recent research assembled a quadcopter with limited financial resources to conduct surveillance in [12]. In contemporary professional settings, individuals engaged in drone piloting or academic research predominantly engage in the construction of drones by utilizing commercially accessible frames and structural designs.…”

Section: Introduction 1scopic Overviewmentioning

confidence: 99%

Quadcopter Unmanned Aerial Vehicle Structural Design Using an Integrated Approach of Topology Optimization and Additive Manufacturing

Al-Haddad,

Jaber,

Giernacki

et al. 2024

Designs

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The performance of quadcopter frames, particularly in terms of weight and crash resistance, is significantly influenced by their structural design and manufacturing process. In this work, a methodology is proposed that integrates advanced principles of topology optimization (TO) and additive manufacturing (AM) techniques to optimize the frame structure for improved performance. First, an analysis is conducted to evaluate existing quadcopter frame configurations, identifying areas for improvement. Experimental evaluations of thrust and moment of motors are performed to assess the performance of the enhanced quadcopter frame, with a focus on advancing the design through computer-aided simulations of static structural analysis and impact tests. The TO technique is then employed to determine the optimal distribution of material within the frame, governed by constraints such as weight reduction and mechanical strength. The results demonstrate that the overall performance of a quadcopter frame is significantly improved by the proposed methodology, showcasing advancements in stability, weight reduction, and crashworthiness. The resulting optimized frame design is subsequently manufactured using AM methods, which offer advantages such as design flexibility and the ability to produce complex geometries. The findings of this study contribute to the field of quadcopter design and optimization by highlighting the synergies between TO and AM techniques. An avenue is offered for the development of lightweight and robust quadcopter frames, as the capabilities and performance of quadcopter systems are advanced. The insights gained from this research open up opportunities for further advancements in the design and manufacturing of UAVs.

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Investigation of Frequency-Domain-Based Vibration Signal Analysis for UAV Unbalance Fault Classification

Cited by 15 publications

References 20 publications

Vibration Signal Processing for Multirotor UAVs Fault Diagnosis: Filtering or Multiresolution Analysis?

Vibration Signal Processing for Multirotor UAVs Fault Diagnosis: Filtering or Multiresolution Analysis?

Enhancing Wind Tunnel Computational Simulations of Finite Element Analysis Using Machine Learning-Based Algorithms

Quadcopter Unmanned Aerial Vehicle Structural Design Using an Integrated Approach of Topology Optimization and Additive Manufacturing

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