In order to improve the three-dimensional positioning accuracy of sensor to converter station inspection robots in unknown environments, a three-dimensional positioning algorithm for converter station inspection based on multi-sensor filtering was studied. Construct a motion information sensing model for the inspection robot in the converter station based on correcting multiple sensors, and use laser radar sensors and IMU sensors to respectively sense the three dimensional coordinate information, angular velocity, and acceleration information of the inspection robot in the converter station; Use the multi sensor correction method based on neural networks to correct the drift error of perceptual information; Through the inspection 3D positioning algorithm based on Kalman filter, the corrected perceptual positioning information is fused and filtered, and the 3D coordinates of the inspection robot in the converter station are estimated to complete the auxiliary work of the inspection 3D positioning in the converter station. In the experiment, the algorithm can locate the dynamic three-dimensional coordinates of the inspection robot in the converter station, and the mean square error of the positioning results is less than 0.05.
KEYWORDS: Inspection, 3D modeling, Inspection equipment, Data modeling, Intelligence systems, Instrument modeling, Data communications, Control systems, Neural networks, Design and modelling
Design a three-dimensional digital intelligent patrol system for substation based on digital twin technology, and intelligently patrol the substation equipment to effectively excavate the potential safety hazards of the substation. The physical entity layer uses cameras and sensors to collect the image of substation equipment, parameter data and environmental information, and carries out effective preprocessing of the acquired data; The digital twin virtual model layer calls the relevant data of the physical entity layer, and uses SolidWorks, 3D MAX and Unity3D software to build the digital twin virtual model of the substation; The application layer plans the patrol path and identifies the electronic tag of the equipment according to the substation data sent by the network transmission layer. On this basis, the patrol module applies the Super SAB neural network equipment state perception and prediction method to effectively perceive and predict the status of the substation equipment, and visualizes the patrol results on the human-computer interaction layer. The experimental results show that the system can effectively inspect the substation equipment, present the inspection results through virtual vision, intelligently inspect the substation equipment, and apply it to practical work, which can achieve better intelligent inspection results in the substation.
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.