scholarly journals Robust Detection, Classification and Localization of Defects in Large Photovoltaic Plants Based on Unmanned Aerial Vehicles and Infrared Thermography

2020 ◽  
Vol 10 (17) ◽  
pp. 5948 ◽  
Author(s):  
Alberto Fernández ◽  
Rubén Usamentiaga ◽  
Pedro de Arquer ◽  
Miguel Ángel Fernández ◽  
D. Fernández ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Infrared Thermography ◽  
Large Scale ◽  
Cost Effective ◽  
Electrical Performance ◽  
Performance Measurements ◽  
Robust Detection ◽  
Aerial Vehicles ◽  
Pv Modules

The efficiency and profitability of photovoltaic (PV) plants are highly controlled by their operation and maintenance (O&M) procedures. Today, the effective diagnosis of any possible fault of PV plants remains a technical and economic challenge, especially when dealing with large-scale PV plants. Currently, PV plant monitoring is carried out by either electrical performance measurements or image processing. The first approach presents limited fault detection ability, it is costly and time-consuming, and it is incapable of fast identification of the physical location of the fault. In the second approach, Infrared Thermography (IRT) imaging has been used for the characterization of PV module failures, but their setup and processing are rather complex and an experienced technician is required. The use of Unmanned Aerial Vehicles (UAVs) for IRT imaging of PV plants for health status monitoring of PV modules has been identified as a cost-effective approach that offers 10–-15 fold lower inspection times than conventional techniques. However, previous works have not performed a comprehensive approach in the context of automated UAV inspection using IRT. This work provides a fully automated approach for the: (a) detection, (b) classification, and (c) geopositioning of the thermal defects in the PV modules. The system has been tested on a real PV plant in Spain. The obtained results indicate that an autonomous solution can be implemented for a full characterization of the thermal defects.

scholarly journals Supplementary material to "Characterization of the Particle Emission from Ships Operating at Sea Using Unmanned Aerial Vehicles"

2017 ◽  
Author(s):  
Tommaso F. Villa ◽  
Reece Brown ◽  
E. Rohan Jayaratne ◽  
L. Felipe Gonzalez ◽  
Lidia Morawska ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Particle Emission ◽  
Aerial Vehicles ◽  
Supplementary Material

In-Flight Detection of Vibration Anomalies in Unmanned Aerial Vehicles

2020 ◽  
Vol 3 (4) ◽  
Author(s):  
Portia Banerjee ◽  
Wendy A. Okolo ◽  
Andrew J. Moore
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Promising Technique ◽  
Bearing Faults ◽  
Vibration Sensors ◽  
Aerial Vehicles ◽  
Flight Operations ◽  
Small Uav ◽  
Close Proximity ◽  
Identification And Characterization

Abstract Owing to the frequency of occurrence and high risk associated with bearings, identification, and characterization of bearing faults in motors via nondestructive evaluation (NDE) methods have been studied extensively, among which vibration analysis has been found to be a promising technique for early diagnosis of anomalies. However, a majority of the existing techniques rely on vibration sensors attached onto or in close proximity to the motor in order to collect signals with a relatively high SNR. Due to weight and space restrictions, these techniques cannot be used in unmanned aerial vehicles (UAVs), especially during flight operations since accelerometers cannot be attached onto motors in small UAVs. Small UAVs are often subjected to vibrational disturbances caused by multiple factors such as weather turbulence, propeller imbalance, or bearing faults. Such anomalies may not only pose risks to UAV’s internal circuitry, components, or payload, they may also generate undesirable noise level particularly for UAVs expected to fly in low-altitudes or urban canyon. This paper presents a detailed discussion of challenges in in-flight detection of bearing failure in UAVs using existing approaches and offers potential solutions to detect overall vibration anomalies in small UAV operations based on IMU data.

scholarly journals Methodological Ambiguity and Inconsistency Constrain Unmanned Aerial Vehicles as A Silver Bullet for Monitoring Ecological Restoration

2019 ◽  
Vol 11 (10) ◽  
pp. 1180 ◽  
Author(s):  
Todd M. Buters ◽  
Philip W. Bateman ◽  
Todd Robinson ◽  
David Belton ◽  
Kingsley W. Dixon ◽  
...  
Keyword(s):  
Machine Learning ◽  
Unmanned Aerial Vehicles ◽  
Ecological Restoration ◽  
Large Scale ◽  
Ecological Monitoring ◽  
Policy Framework ◽  
Strong Positive Correlation ◽  
Aerial Vehicles ◽  
The Future ◽  
Thermal Cameras

The last decade has seen an exponential increase in the application of unmanned aerial vehicles (UAVs) to ecological monitoring research, though with little standardisation or comparability in methodological approaches and research aims. We reviewed the international peer-reviewed literature in order to explore the potential limitations on the feasibility of UAV-use in the monitoring of ecological restoration, and examined how they might be mitigated to maximise the quality, reliability and comparability of UAV-generated data. We found little evidence of translational research applying UAV-based approaches to ecological restoration, with less than 7% of 2133 published UAV monitoring studies centred around ecological restoration. Of the 48 studies, > 65% had been published in the three years preceding this study. Where studies utilised UAVs for rehabilitation or restoration applications, there was a strong propensity for single-sensor monitoring using commercially available RPAs fitted with the modest-resolution RGB sensors available. There was a strong positive correlation between the use of complex and expensive sensors (e.g., LiDAR, thermal cameras, hyperspectral sensors) and the complexity of chosen image classification techniques (e.g., machine learning), suggesting that cost remains a primary constraint to the wide application of multiple or complex sensors in UAV-based research. We propose that if UAV-acquired data are to represent the future of ecological monitoring, research requires a) consistency in the proven application of different platforms and sensors to the monitoring of target landforms, organisms and ecosystems, underpinned by clearly articulated monitoring goals and outcomes; b) optimization of data analysis techniques and the manner in which data are reported, undertaken in cross-disciplinary partnership with fields such as bioinformatics and machine learning; and c) the development of sound, reasonable and multi-laterally homogenous regulatory and policy framework supporting the application of UAVs to the large-scale and potentially trans-disciplinary ecological applications of the future.

A comparative study of greywater from domestic and public buildings

2013 ◽  
Vol 14 (1) ◽  
pp. 135-141 ◽  
Author(s):  
C. Santos ◽  
C. Matos ◽  
F. Taveira-Pinto
Keyword(s):  
Urban Areas ◽  
Large Scale ◽  
Potable Water ◽  
Cost Effective ◽  
Public Buildings ◽  
Correct Definition ◽  
Cost Effective Treatment ◽  
Negative Impacts ◽  
Definition Of

Greywater (GW) can be an important resource for urban water consumption, replacing potable water for purposes that do not require drinking water quality. If applied on a large scale, this practice will reduce the potable water demand and the wastewater produced in urban areas, minimizing the negative impacts and costs of water extraction and wastewater treatment. A correct characterization of GW is important to assess its potential for a direct reuse or, if not possible, to make a correct definition of a feasible and cost-effective treatment system. This article aims to contribute to the characterization of GW produced in washbasins and showers in domestic and public buildings. A compilation of several works on GW collection and sampling produced by the authors is presented. Samples were taken from GW produced in showers and washbasins in households, changing rooms and in a restaurant. Results are compared with values presented in similar studies and compared with standards and guidelines published in different countries.

scholarly journals POST-FIRE FORESTRY RECOVERY MONITORING USING HIGH-RESOLUTION MULTISPECTRAL IMAGERY FROM UNMANNED AERIAL VEHICLES

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 301-305 ◽  
Author(s):  
L. Pádua ◽  
T. Adão ◽  
N. Guimarães ◽  
A. Sousa ◽  
E. Peres ◽  
...  
Keyword(s):  
High Resolution ◽  
Unmanned Aerial Vehicles ◽  
Tree Height ◽  
Ground Truth ◽  
Cost Effective ◽  
Forest Disturbances ◽  
Ground Truth Data ◽  
High Resolution Data ◽  
Aerial Vehicles ◽  
Fire Scenarios

<p><strong>Abstract.</strong> In recent years unmanned aerial vehicles (UAVs) have been used in several applications and research studies related to environmental monitoring. The works performed have demonstrated the suitability of UAVs to be employed in different scenarios, taking advantage of its capacity to acquire high-resolution data from different sensing payloads, in a timely and flexible manner. In forestry ecosystems, UAVs can be used with accuracies comparable with traditional methods to retrieve different forest properties, to monitor forest disturbances and to support disaster monitoring in fire and post-fire scenarios. In this study an area recently affected by a wildfire was surveyed using two UAVs to acquire multi-spectral data and RGB imagery at different resolutions. By analysing the surveyed area, it was possible to detect trees, that were able to survive to the fire. By comparing the ground-truth data and the measurements estimated from the UAV-imagery, it was found a positive correlation between burned height and a high correlation for tree height. The mean NDVI value was extracted used to create a three classes map. Higher NDVI values were mostly located in trees that survived that were not/barely affected by the fire. The results achieved by this study reiterate the effectiveness of UAVs to be used as a timely, efficient and cost-effective data acquisition tool, helping for forestry management planning and for monitoring forest rehabilitation in post-fire scenarios.</p>

scholarly journals Behaviour reactions of bottlenose dolphins (Tursiops truncatus) to multirotor Unmanned Aerial Vehicles (UAVs)

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ticiana Fettermann ◽  
Lorenzo Fiori ◽  
Martin Bader ◽  
Ashray Doshi ◽  
Dan Breen ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Tursiops Truncatus ◽  
Bottlenose Dolphins ◽  
Cost Effective ◽  
Aerial Survey ◽  
Cetacean Species ◽  
Age Class ◽  
Aerial Vehicles ◽  
Vtol Uav ◽  
Aerial Observation

Abstract Unmanned aerial vehicles (UAVs) represent a novel and cost effective research tool to investigate cetacean behaviour, as conventional aircraft are expensive, limited in the altitude they can fly at and potentially disturb sensitive wildlife. In addition, the aerial observation from the UAVs allows assessment of cetacean behaviour from an advantageous perspective and can collect high spatial and temporal resolution data, providing the opportunity to gather accurate data about group size, age class and subsurface behaviour. However, concerns have been raised about the potential risks of disturbance to animals caused by the UAV’s visual and acoustic stimuli. Boat-based surveys were conducted to assess the short-term behavioural responses of resting bottlenose dolphins (Tursiops truncatus) to a lightweight Vertical take-off and landing (VTOL) UAV flown at 10, 25, and 40 m altitude. Changes in group swim direction and frequencies of surface and aerial behavioural events were recorded from an anchored research vessel before (control) and during the aerial survey. The number of reorientation and tail slap events increased significantly between controls and flights when the UAV was flown at 10 m over the animals. In contrast, no significant differences were detected when the aircraft was flown at 25 and 40 m altitude. However, a precautionary approach is recommended for research applications requiring lower flight altitudes, with further research recommended to assess how different cetacean species and age class may respond to the UAV presence.

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