Injection molding machine energy consumption abnormity detection method and system based on Gaussian mixture model

Abstract

The invention discloses an injection molding machine energy consumption abnormity detection method and system based on a Gaussian mixture model, and the method comprises the steps: carrying out the real-time collection of the energy consumption data of a first injection molding machine, and obtaining the first real-time energy consumption data; performing data preprocessing on the first real-time energy consumption data to obtain second real-time energy consumption data; inputting the second real-time energy consumption data into a Gaussian mixture model for clustering feature learning to obtain a first clustering data set and generate a first mark training data set; performing model training according to the first mark training data set to obtain a first anomaly detection model; and inputting a first test training data set of the first injection molding machine into the first anomaly detection model to obtain first output information. The technical problem that in the prior art, when the energy consumption abnormity of the industrial injection molding machine is detected, due to the fact that data features are not comprehensive and perfect enough, multi-dimensional data classification is not accurate enough, and the false alarm rate is high, the detection precision is not high is solved.

Description

technical field [0001] The invention relates to computer-related fields, in particular to a method and system for detecting abnormal energy consumption of an injection molding machine based on a Gaussian mixture model. Background technique [0002] Injection molding machine is the key equipment for the production of plastic products. Traditional fully hydraulically driven injection molding machines play a leading role in the industry. The power of this type of injection molding machine mainly comes from the quantitative pump driven by a three-phase asynchronous motor at constant speed. Each stage of the injection molding process depends on The valve control of the hydraulic system is completed, and the required flow and pressure of each stage are constantly changing, resulting in serious high-pressure throttling and overflow loss, so that the full hydraulic drive injection molding machine consumes a lot of energy. Therefore, energy saving, high efficiency and precision are t...

AI Technical Summary

Problems solved by technology

[0005] The embodiment of the present application provides a Gaussian mixture model-based method and system for detecting abnormal energy consumption of injection molding machines, which solves the problem of inaccurate classification of multi-dimensional data due to insufficient comprehensiveness and perfection of data characteristics in the detection of abnormal energy consumption of industrial injection molding machines in the prior art. , the false alarm rate is high, leading to the technical problem of low detection accuracy, and achieved the technical effect of extracting the optimal characteristics of data classification, thereby improving the abnormal detection accuracy of the energy consumption of the injection molding machine and reducing the false alarm rate.

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