Product quality alarm method and device based on integrated learning

Abstract

The embodiment of the present disclosure discloses a product quality alarm method and device based on integrated learning. A specific embodiment of the method includes: detecting whether an operation authorization signal is received from the target terminal device; in response to detecting the operation authorization signal, detecting and acquiring an initial product quality sample data set, wherein the initial product quality sample data set includes the initial product quality Physical and chemical index data sets, initial product gas emission index data sets, and initial product evaluation result data sets; generate target product quality sample data sets; input target product quality sample data sets into predetermined prediction models to obtain prediction result sets; predict The result set is pushed to the target terminal device to control the target terminal device to perform alarm-related operations. This embodiment uses a predetermined prediction model to perform quality analysis on the acquired initial product quality sample data set, which can improve the accuracy of quality prediction results and improve the level of product quality control.

Description

technical field [0001] Embodiments of the present disclosure relate to the field of computer technology, and in particular to information processing methods and devices. Background technique [0002] The internal quality of cigarettes, such as sensory quality, is closely related to certain physical and chemical components in cigarettes. These physical and chemical components determine the internal quality of cigarettes to a certain extent, such as nicotine in tobacco and sensory stimulation. Feature related. Domain experts often need to refer to these detected components when performing sensory evaluations. Tobacco leaves contain numerous chemical constituents. The interaction of various chemical components in the smoking process stimulates people's senses of taste, smell, and touch, all of which are extremely complex. How to analyze the chemical composition, sensory evaluation and smoke of tobacco leaves is of great significance to reduce the production design cost of en...

AI Technical Summary

Problems solved by technology

Controlling the internal quality of cigarettes in the case of small sample data has the problem of low quality control level, and then there is a risk of quality control failure, which makes false alarms for low-quality cigarette products

[0005] Second, the amount of sample data for cigarette quality control is small, and the accuracy of using a single model to learn small sample data is low, which cannot meet the requirements of cigarette quality control, which in turn affects the triggering of low-quality cigarette alarms

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