Vertical mill vibration prediction method and device based on ARIMA and RNN

Abstract

The embodiment of the invention provides a vertical mill vibration prediction method and device based on ARIMA and RNN, and belongs to the technical field of vertical mill vibration prediction. The method comprises the following steps: acquiring first time series data representing a real-time vibration value of a vertical mill and second time series data representing a real-time value of an influence factor; establishing a first time sequence matrix representing the incidence relation between the vibration value of the vertical mill and the influence factor; taking the first time series data as input, and outputting third time series data for predicting a future vibration value of the vertical mill through an ARIMA autoregressive moving average model; taking the first time sequence matrixas input, and outputting fourth time sequence data for predicting a residual error of a future vibration value of the vertical mill through an RNN recurrent neural network model; summing the third time series data and the fourth time series data, and outputting fifth time series data for finally predicting a future vibration value of the vertical mill. According to the method, through ARIMA and RNN hybrid modeling, the problem that in the prior art, the hysteresis quality is large in the real-time production process is solved.

Description

technical field [0001] The invention relates to the technical field of vertical mill vibration prediction, in particular to a vertical mill vibration prediction method based on ARIMA and RNN and a vertical mill vibration prediction device based on ARIMA and RNN. Background technique [0002] The cement industry is a relatively typical high-energy-consuming and energy-dependent industry. In the cement production process, the grinding operation of raw materials, coal and slag is an important energy consumption link, accounting for about 50%-60% of the total energy consumption. , so the research and improvement of grinding equipment and related process parameters is a hot spot in the cement industry. As a major improvement of grinding equipment, vertical mills can use energy more efficiently and improve production efficiency compared with traditional ball mills, and have been fully promoted and applied in the cement field. In actual production practice, the vibration value of ...

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Problems solved by technology

[0003] The purpose of the embodiment of the present invention is to mine the linear relationship in the vertical mill vibration time-series data flow based on the ARIMA autoregressive moving average model, and combine the RNN cyclic neural network to capture the relationship between the vertical mill vibration residual time-series flow and the impact factors after linear extraction. The non-linear relationship realizes the online prediction of the vibration value of the vertical mill, so as to solve the problem in the prior art that the parameters or inspections need to be artificially found after the vibration value is abnormal, and there is a large hysteresis in the real-time production process

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