Multi-time scale convolutional neural network soft measurement method based on attention mechanism

Abstract

The invention relates to a multi-time scale convolutional neural network soft measurement method based on an attention mechanism, and belongs to the technical field of soft measurement. The method comprises the following steps: 1, determining an auxiliary variable, carrying out data processing, selecting an easily-measured variable related to a difficult-to-measure parameter as the auxiliary variable of a soft measurement model, and collecting a time sequence of the auxiliary variable and the difficult-to-measure parameter; abnormal value elimination is carried out on the collected time sequence; 2, selecting an attention mechanism and an attention area, and dividing the attention area according to the time delay and the effective time scale of each auxiliary variable relative to the difficult-to-measure parameters; 3, constructing the input of a soft measurement model, forming a matrix by the time sequence of each auxiliary variable, and determining the input of the soft measurement model by combining the attention area of the attention mechanism; 4, establishing a time sequence convolutional neural network soft measurement model; 5, training a time sequence convolutional neural network soft measurement model; and 6, carrying out real-time estimation on unmeasured parameters by utilizing the time sequence convolutional neural network model trained in the step 5.

Description

technical field [0001] The invention relates to a multi-time-scale convolutional neural network soft-sensing method based on an attention mechanism, and belongs to the field of soft-sensing technology. Background technique [0002] In the modern industrial production process, in order to realize energy saving and benefit maximization, it is of great significance to monitor and control the important parameters in the production process in time. Usually, for important parameters in the industrial production process, there are mainly two measurement methods: on-line measurement and off-line measurement. On-line measurement refers to the use of instruments to directly measure parameters, but the equipment is expensive, difficult to maintain, and the accuracy of measurement results is easily affected by on-site working conditions. Off-line measurement refers to the measurement of parameters by the method of offline inspection, but offline inspection often takes a long time, resu...

AI Technical Summary

Problems solved by technology

On-line measurement refers to the use of instruments to directly measure parameters, but the equipment is expensive, difficult to maintain, and the accuracy of measurement results is easily affected by on-site conditions

Offline measurement refers to the measurement of parameters by the method of offline inspection, but offline inspection often takes a long time, resulting in a large delay in the guidance of the production process by the measurement results obtained offline

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