Catenary Intelligent Inspection Robot

OCLIS1000

With the continuous expansion of metro operation scale, the number of equipment and facilities is growing geometrically, and the maintenance workload of catenary is also doubling. However, the traditional manual inspection method has some problems, such as high work intensity, low efficiency and inaccuracy. Therefore, Hangzhou Shenhao Technology Co., LTD., aiming at the catenary inspection of rail transit, developed the catenary intelligent inspection robot. The product is mainly used in the field of urban rail transit, suitable for the urban rail line using catenary as the power supply means. Running on the convergence bar of catenary, the robot is capable of autonomous movement, detection and analysis, high-precision measurement of catenary contact surface width, wear allowance and deflection angle, identification and positioning of surface damage defects such as wire drawing on the surface of the contact line, analysis results and real-time display, real-time storage, export reports and other functions. The successful development of catenary intelligent inspection robot can realize the intelligent detection and big data management of catenary system, greatly improve inspection efficiency and reduce operation and maintenance costs.

SHENGHAO

Load ng

Reduce the intensity of inspection work

The traditional manual inspection method of manual measurement and visual inspection is inefficient, intensive and poorly standardised. With the use of robots, inspection results can be viewed remotely via handheld terminals.
Reducing personnel risk

Traditional manual inspection requires continuous climbing and poses a safety risk. With robots, there is no need to work continuously at height and the personal safety of the inspectors is guaranteed.
Standardising data

As a standardised collection device, the robot's continuous inspection results are not affected by differences in personnel operations, enabling consistency and continuity of data and the traceability, analysis and review of inspection data.
Improve inspection efficiency

Traditional manual inspection requires 2km of random position wear measurement per night and 4 weeks to complete the full line. With the robot, it is possible to inspect a distance of 8km per night, taking only 1 week to complete the entire line. The overall inspection efficiency is increased to 16 times (8/2 x 4/1).
Big data analysis

By establishing a big data analysis platform, professional data analysis functions such as data statistics, analysis, enquiry and export are completed. Automated analysis, management, alerting and forecasting of inspection data effectively improves process efficiency and assists customers in maintenance decisions.
Artificial intelligence detection algorithms

The contact line surface defect detection function uses deep learning technology to quickly and accurately identify defects of millimetre width on the contact line surface.
Highly accurate wear measurement algorithms

Based on the collected 3D data, the high-precision measurement algorithm is highly resistant to interference and can adapt to environmental disturbances such as oil and debris.