BP neural network coal conveying fault prediction method based on genetic algorithm optimization

Abstract

The invention discloses a BP neural network coal conveying fault prediction method based on genetic algorithm optimization. The method comprises the following steps: determining a BP neural network topological structure diagram; taking harbor office unit parameters as input variables in the BP neural network topological structure diagram, and performing data normalization processing to obtain an initial population; coding individual chromosomes in the initial population, and evaluating the fitness value of each chromosome; selecting excellent individuals according to the fitness values, and performing selection, crossover and mutation operation to obtain an optimal individual; establishing an improved BP network learning rate optimization model for optimally calculating a BP neural network weight and a threshold value; and decoding by using the optimal individual and assigning the optimal individual to the BP neural network as network initial weight and threshold input, and training the neural network to obtain an optimal prediction model. The coal conveying system fault can be predicted in advance, software and hardware are easy to implement, the cost is low, the convergence speed of a traditional neural network is increased, and the network training efficiency is improved.

Description

technical field [0001] The invention relates to a fault prediction technology in the field of computers, in particular to a BP neural network coal conveying fault prediction method based on genetic algorithm optimization. Background technique [0002] In the coal transportation system of the Port Authority, the motor drives the conveyor belt to run through the reducer and the coupler. The coupler is located between the motor and the reducer and is flexibly connected to the motor to protect the motor. When the load is overloaded, the reducer stops, but the motor drives the coupler to still run. At this time, the oil temperature inside the coupler will rise sharply, and the temperature rise will cause a large change. If measures are not taken in time, it will cause Motor equipment damage accident, resulting in loss of property of the Port Authority. [0003] The current measure is to add a substance with a certain temperature and melting point in the coupler. When the materi...

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Problems solved by technology

[0004] Aiming at the deficiencies in the prior art that the protection equipment of the coal transportation system is passive protection, and failures cannot be predicted, the problem to be solved by the present invention is to provide a method that can effectively improve the accuracy of failure prediction of the coal transportation system and change passive protection into active protection. Protected BP Neural Network Coal Transportation Fault Prediction System and Method

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