Method and device for building equipment risk recognition model

Abstract

An embodiment of the invention discloses a method and a device for building an equipment risk recognition model. The method includes the steps: acquiring first sample data from an internet of things cloud platform; processing the first sample data, and dividing the processed first sample data into training set data and testing set data; training the equipment risk recognition model by the aid of the training set data to obtain a target equipment risk recognition model; testing the target equipment risk recognition model by the aid of the testing set data to obtain accuracy rate of the target equipment risk recognition model; judging whether the accuracy rate is higher than a preset threshold value or not; determining a fact that identification rate of the target equipment risk recognitionmodel reaches a standard if the accuracy rate is higher than the preset threshold value. Total sample data contain the first sample data and are uploaded to the internet of things cloud platform, andthe equipment risk recognition model is a pre-built equipment risk recognition model to be trained.

Description

technical field [0001] The embodiments of the present application relate to the computer field, and in particular, relate to a method for establishing an equipment risk identification model, an apparatus for establishing an equipment risk identification model, and a computer-readable storage medium. Background technique [0002] With the development of science and technology, equipment is used in many production fields. However, due to the complex operating environment of the equipment and the aging of equipment parts due to the long running time of the equipment, the occurrence of equipment failure has become inevitable and accidental. Therefore, in order to ensure The stable and efficient operation of the equipment requires the identification of the risks of the equipment, the timely detection of the risks of the equipment, and the reduction of the failure rate of the equipment. [0003] In order to reduce the impact of equipment failure on the user's production operations...

AI Technical Summary

Problems solved by technology

[0004] However, the equipment risk identification model based on statistical methods depends on the quality of sample data. If there is no high-quality, high-characteristic sample data, the accuracy of the data predicted by the equipment risk identification model will be low.

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