Overhead crane steel rail is a critical component of overhead crane systems, and its condition directly impacts operational safety and efficiency.

When the overhead crane is in normal operation, the wheel rim and the overhead crane steel rail should maintain a certain gap (20 mm-30 mm). In the production practice, the problem of steel rail gnawing has always been a problem that affects its normal operation.

It reduces the working efficiency of the equipment, increases the maintenance workload and operating cost, and leads to safety hazards, causing adult or equipment accidents.

Therefore, it is very important to detect the status of the steel rail for the overhead crane in time and repair or replace it in advance to prevent a larger accident.

At present, there are mainly two methods for judging the crane steel rail.

1. The experience method.

The empirical method is mainly based on the phenomenon caused by the previous crane steel rail to judge whether the current overhead crane rail is broken, such as obvious friction marks on the side of the crane steel rail, the increased running resistance of the crane, etc. The accuracy of this method is poor, and the wheel detection method is adopted.

2. The wheel detection method.

The detection system mainly includes three parts, namely the total station, the orbit detection robot, and the reconstruction computing system. The orbit detection robot carries the corner prism along the track, the distance from the prism to the side of the track remains unchanged, and the total station tracks and records the position of the prism in real time.

Through the data processing, the top line of the top surface of the two rails can be reconstructed, and the straightness of the crane track, the parallelism of the two rails, the track span, and other parameters are calculated.

The system is designed according to the cross-sectional dimensions of common rails and is suitable for crane rails with a width of 70 mm-130 mm and heavy rails with widths of 68 mm and 70 mm. The measurement accuracy is +/-2 mm. The detection speed is 0.2-0.3 m/s, so the detection efficiency can be greatly improved.