Aimed at disadvantages of incomprehensive safety assessment and low alarm accuracy in traditional climbing scaffold control system

put forward a method to improve safety warning performance of climbing scaffold control system by multi-sensor data fusion technology. The method acquires data of load

oblique angle and rising velocity of climbing scaffold through sensors

fuse data by using BP neural network and then evaluate safety of system. Describe fusion algorithm in detail

training process

system hardware and software realization. The test results show that the method not only can assess security of system from multi-angle

but also can improve alarm accuracy of climbing scaffold control system

so as to improve reliability of the system.