基于高斯受限玻尔兹曼机的工业产品质量智能异常检测

doi:10.3969/j.issn.1007-7375.2022.06.018

工业工程 ›› 2022, Vol. 25 ›› Issue (6): 152-159.doi: 10.3969/j.issn.1007-7375.2022.06.018

基于高斯受限玻尔兹曼机的工业产品质量智能异常检测

黄聪¹, 农英雄¹, 张毅²

1. 广西中烟信息中心，广西南宁 530001;
2. 清华大学自动化系，北京 100018

收稿日期:2021-06-04 发布日期:2022-12-23
作者简介:黄聪(1974—)，男，广西壮族自治区人，高级工程师，硕士，主要研究方向为信息化管理及信息系统开发

Intelligent Anomaly Detection for Industrial Product Quality Inspection Based on Gaussian Restricted Boltzmann Machine

HUANG Cong¹, NONG Yingxiong¹, ZHANG Yi²

1. Guangxi China Tobacco Industry Co., Ltd., Nanning 530001, China;
2. Department of Automation, Tsinghua University, Beijing 100018, China

Received:2021-06-04 Published:2022-12-23

摘要/Abstract

摘要： 为了提升基于复杂数据特征的工业产品质量异常检测性能，利用高斯受限玻尔兹曼机在高维数据非线性建模和计算复杂性上的综合优势，提出一种智能异常检测方法FE-GRBM。利用GRBM模型中自由能量与边缘概率自然对数的数学关系，设计基于自由能量的模型训练及检测策略。通过真实烟支成品质量检测案例开展实验验证。结果显示，FE-GRBM平均性能高于3个传统方法最高分0.29，高于RE-GRBM 0.04，验证了方法的有效性和优越性。

关键词: 异常检测, 受限玻尔兹曼机, 自由能量函数, 质量检测, 烟支产品

Abstract: In order to improve the quality anomaly detection performance of industrial products based on complex data features, an intelligent anomaly detection method FE-GRBM for industrial product quality inspection is proposed based on the comprehensive advantages of Gaussian Restricted Boltzmann machine in nonlinear modeling and computational complexity. Specifically, the free energy based model training and detection strategies are studied, using the mathematical relationship between free energy and natural logarithm of edge probability of GRBM. The method are verified by the quality inspection of cigarette products in real case. The results show that the average performance of FE-GRBM is 0.29 higher than the highest score among the three traditional methods, and 0.04 higher than that of RE-GRBM, which shows the superiority of our method.

Key words: anomaly detection, restricted Boltzmann machine (RBM), free-energy function, quality inspection, cigarette products

中图分类号:

TS452

黄聪, 农英雄, 张毅. 基于高斯受限玻尔兹曼机的工业产品质量智能异常检测[J]. 工业工程, 2022, 25(6): 152-159.

HUANG Cong, NONG Yingxiong, ZHANG Yi. Intelligent Anomaly Detection for Industrial Product Quality Inspection Based on Gaussian Restricted Boltzmann Machine[J]. Industrial Engineering Journal, 2022, 25(6): 152-159.

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基于高斯受限玻尔兹曼机的工业产品质量智能异常检测

Intelligent Anomaly Detection for Industrial Product Quality Inspection Based on Gaussian Restricted Boltzmann Machine

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