Equipment lifetime prediction method and system based on PSO-BP neural network

Abstract

The invention discloses an equipment lifetime prediction method and system based on a PSO-BP neural network, and belongs to equipment lifetime prediction. The method comprises the following steps: 1) constructing a data set by acquiring lifetime cycle data of equipment, and performing normalization processing; 2) constructing a BP neural network; 3) taking the weight and the threshold of the BP neural network as dimension components of particles, initializing parameters of a particle swarm algorithm, and determining an individual optimal position, an optimal fitness, a global optimal position and a fitness; 4) training the data set by adopting the BP neural network, and screening out optimal particles, namely the optimal weight and threshold value of the network, from an obtained result through the particle swarm algorithm; 5) taking the result of the particle swarm algorithm as an initial weight and a threshold value of the network for training until a minimum error condition or a maximum training frequency is met; and 6) predicting equipment data by using the trained network, and outputting the predicted service lifetime of the equipment. Compared with other technologies, the method has the advantage that the service lifetime of the equipment can be quickly and accurately predicted.

Description

technical field [0001] The invention belongs to the field of equipment life prediction, and more particularly relates to a method and system for equipment life prediction based on PSO-BP neural network. Background technique [0002] With the continuous development of science and technology and all aspects of society, the level of industrial production in our country has been significantly improved. Nowadays, the development trend of intelligent, large-scale and high-speed equipment has become more obvious, and the daily maintenance of equipment will become more difficult. The result of intelligent and large-scale equipment is that the operation of the equipment is closely linked, and the various processes are closely coordinated, which makes it more difficult to repair the failures directly caused by wear or aging during the normal operation of the equipment, and once there is a problem in the operation of the equipment At the least, the suspension of production will cause ...

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Problems solved by technology

[0004] Aiming at the defects of the related technology, the object of the present invention is to provide a PSO-BP neural network-based equipment life prediction method and system, aiming at solving the problem that the existing prediction method cannot quickly and accurately complete the prediction of the equipment life due to the unknown degradation model of the equipment. problem of forecasting

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