Damage Degree Evaluation of Earthquake Area Using UAV Aerial Image

Chen, Jinhong; Liu, Haoting; Zheng, Jie; Liu, Ming; Yan, Beibei; Hu, Xin; Gao, Yinjie

doi:10.1155/2016/2052603

Cited by 35 publications

(14 citation statements)

References 21 publications

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“…Its inputs have the image features, the imaging thermophysical property features, and the laser parameters. Table 1 Regarding the image features, first, the GLCM features [31] are computed. Obviously, they can represent the texture information of corrosive metal.…”

Section: Preliminary Control Of Cleaning Effectmentioning

confidence: 99%

Automatic Process Parameters Tuning and Surface Roughness Estimation for Laser Cleaning

Liu

Yang

et al. 2020

IEEE Access

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An image analysis-based two-stage process parameters tuning and Surface Roughness (SR) estimation algorithm is proposed for the laser cleaning application. A Cartesian coordinate robot is utilized to collect image and implement cleaning. Before cleaning, in order to tune the proper laser parameters, first, the environment lighting is controlled for the metal image collection. Second, lots of classification features are computed for the images above. The Gray-Level Co-occurrence Matrix (GLCM) texture features, the concavo-convex region features, the histogram symmetry difference feature, and the imaging thermophysical property features are computed. Third, the initial laser parameters are created randomly and an iteration computation is performed: a Support Vector Machine (SVM) is used to forecast the cleaning effect; its inputs include the classification features and the initial laser parameters; its output is the cleaning effect degree. If the SVM output cannot fulfill user's demand, the laser parameters will be updated randomly. This iteration will be implemented constantly until the SVM output becomes valid. Then the laser cleaning will be performed. When estimating SR for the cleaned metal, multiple image features are calculated for the images after cleaning. The features include the Tamura coarseness, some GLCM features, and the convex region feature. To improve the prediction precision, different feature combinations are used for different cleaning effects. The linear function and the 3-order polynomial function are considered for the SR estimation. After tests, the accuracies of SVM, the SR prediction function, and the integrated SR control and estimation algorithm can be 90.0%, 80.0% and 80.0% approximately.

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Section: Preliminary Control Of Cleaning Effectmentioning

confidence: 99%

Automatic Process Parameters Tuning and Surface Roughness Estimation for Laser Cleaning

Liu

Yang

et al. 2020

IEEE Access

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“…In that situation the SFCN will not be used and only the BSCS can be employed. And if both the SFCN and the BSCS cannot be used permanently in a serious situation, the unmanned aerial vehicle (UAV) [17] may be used as a communication relay station for the disaster rescue in future. The UAV can carry the visible light camera to implement the information collection task and it also can take the wireless communication relay terminal to realize the wireless information transmission for other ground equipment.…”

Section: Design Of Hardware Systemmentioning

confidence: 99%

Modeling and Simulation of Scheduling Medical Materials Using Graph Model for Complex Rescue

Lv¹,

Zheng²,

Tong³

et al. 2017

J Inf Process Syst

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A new medical materials scheduling system and its modeling method for the complex rescue are presented. Different from other similar system, first both the BeiDou Satellite Communication System (BSCS) and the Special Fiber-optic Communication Network (SFCN) are used to collect the rescue requirements and the location information of disaster areas. Then all these messages will be displayed in a special medical software terminal. After that the bipartite graph models are utilized to compute the optimal scheduling of medical materials. Finally, all these results will be transmitted back by the BSCS and the SFCN again to implement a fast guidance of medical rescue. The sole drug scheduling issue, the multiple drugs scheduling issue, and the backup-scheme selection issue are all utilized: the Kuhn-Munkres algorithm is used to realize the optimal matching of sole drug scheduling issue, the spectral clustering-based method is employed to calculate the optimal distribution of multiple drugs scheduling issue, and the similarity metric of neighboring matrix is utilized to realize the estimation of backup-scheme selection issue of medical materials. Many simulation analysis experiments and applications have proved the correctness of proposed technique and system.

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“…With the development of mechanical technologies, automation technology, and artificial intelligence, Unmanned Aerial Vehicles (UAVs) are becoming more and more capable in various industries. Owing to its low cost, no risk of casualties, and good maneuverability, it has been widely applied in many scenarios to replace manual tasks in recent years, e.g., remote sensing [1], precision agriculture [2], disaster relief [3], and logistics service [4]. Especially in military operations, UAVs are replacing warriors to undertake more and more work [5], showing its great advantages in concealment, survivability, and diversified capabilities.…”

Section: Introductionmentioning

confidence: 99%

A Damage-Tolerant Task Assignment Algorithm for UAV Swarm in Confrontational Environments

Chen

Bao

Men

et al. 2020

International Journal of Aerospace Engineering

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As Unmanned Aerial Vehicles (UAVs) are widely used in many applications, a lot of military missions in confrontational environments are being undertaken by UAV swarm rather than human beings due to its advantages. In confrontational environments, the reliability and availability of UAV swarm would be the major concern because of UAVs’ vulnerability, so damage-tolerant task assigning algorithms are of great importance. In this paper, we come up with a novel damage-tolerant framework for assigning real-time tasks to UAVs with dynamical states in confrontational environments. Different from existing scheduling methods, we not only assign tasks but also back up copies of tasks to UAVs when needed, to promote reliability. Meanwhile, we adopt an overlapping mechanism, including Backup-Primary overlapping and Backup-Backup overlapping, in assignment to save the limited swarm resources. On the basis of the damage-tolerant and overlapping mechanism, for the first time, we propose a new damage-tolerant task assignment algorithm named DTTA, aiming at promoting the task success probability. Extensive experiments are conducted based on random synthetic workloads to compare DTTA with three baseline algorithms. The experimental results indicate that DTTA can efficiently promote the probability of tasks’ success without affecting the effectiveness of swarms in confrontational environments.

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Damage Degree Evaluation of Earthquake Area Using UAV Aerial Image

Cited by 35 publications

References 21 publications

Automatic Process Parameters Tuning and Surface Roughness Estimation for Laser Cleaning

Automatic Process Parameters Tuning and Surface Roughness Estimation for Laser Cleaning

Modeling and Simulation of Scheduling Medical Materials Using Graph Model for Complex Rescue

A Damage-Tolerant Task Assignment Algorithm for UAV Swarm in Confrontational Environments

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