FIELD: machine building.
SUBSTANCE: invention relates to lifting and transport machine building. To protect tower cranes from roll-over the database of maximum wind speeds in the area of the crane operation is created. On their basis a neural network algorithm is pre-trained in steady-state conditions. An expansion board (2) is connected to the programmable logic controller (1). During the crane operation the wind speed observations, wind direction and boom position are registered. The signals from boom position sensors (4) and wind direction (5) are compared and the mismatch angle is calculated. On the basis of algorithm of the programmable logic controller (1) the future value of wind speed is forecasted. It is compares with the maximum allowable value for the given model of the crane, and using the programmable logic controller (1) the control instruction for actuating of anti-theft grippers (for travelling tower cranes) and the control instruction sent to the actuating devices (7) of the rotation drive (8) for adjustment of the boom position along the shortest path according to the forecasted gust direction are generated, before the rollover moment from the wind load achieves the margin value.
EFFECT: safety improvement.
1 dwg
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Authors
Dates
2015-02-27—Published
2012-12-14—Filed