KEYWORDS: Inspection, Unmanned aerial vehicles, Data transmission, Data modeling, Wireless communications, Network architectures, Control systems, Power grids, Systems modeling, Probability theory
The current transmission line intelligent inspection technology based on differential positioning uses UAVs to achieve inspection of transmission lines through carrier wave differential positioning technology, which leads to low inspection level accuracy due to low carrier wave phase differential accuracy. In this regard, the transmission line wide-area cluster intelligent inspection technology based on hybrid grouping network is proposed. The LTE hybrid network communication environment is constructed, the wireless network coverage is planned, and intelligent inspection information scheduling is carried out. The wireless network topology is controlled, and the cooperative inspection planning of robot and UAV is proposed. In the experiment, the proposed inspection technique is verified for inspection accuracy. The analysis of the experimental results shows that the intelligent inspection technology of transmission lines constructed by the proposed method has a high inspection accuracy.
KEYWORDS: Data transmission, Unmanned aerial vehicles, Inspection, Data modeling, Data storage, Detection and tracking algorithms, Data conversion, Reflection, Tolerancing, Testing and analysis
The current UAV inspection multi-link data congestion control method based on link capacity uses a cache queue model to regulate the data throughput at the sending end, which leads to low control performance due to the lack of monitoring of data sending nodes. In this regard, the transmission line UAV inspection multi-link data congestion control method is proposed. The state of the UAV network data nodes is sensed using an ant colony algorithm, data scheduling flows are selected according to the bandwidth load, and data congestion is alleviated through data allocation as well as route maintenance. In the experiments, the control performance of the proposed control method is verified. The analysis of the experimental results shows that the proposed method is used to construct a multi-link data congestion control technique with a low data congestion rate and its control performance is high.
KEYWORDS: Inspection, Unmanned aerial vehicles, Data transmission, Data communications, Design and modelling, Data modeling, Signal to noise ratio, Mathematical modeling, Wavelets, Denoising
In the process of practical application, constrained by the UAV's own performance and other conditions, some transmission line UAV inspection data low latency back transmission method has the defect of high probability of code element error. In this context, a new method of low latency return transmission line UAV inspection data is designed. Construct the transmission line inspection task allocation model, derive the mathematical expression formula of the distance interval between the stationing point and the target tower in the area to be inspected, describe the probability of priority allocation in the inspection data transmission process, detect the effective bandwidth of the UAV channel, decompose the time delay between the UAV transmission end and the ground receiving end, and design the data low-latency back transmission method. Test result: The mean value of code element error probability of the designed transmission line UAV inspection data low latency return method is 2.214%, which has a higher performance advantage compared to the other two transmission line UAV inspection data low latency return methods.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.