Work

Temperature Abnormality Monitoring Model for Industrial Equipment-Based Image and Infrared Thermography

Year: 2025

Type: book-chapter

Abstract: The study proposed a model for monitoring temperature anomalies in industrial machinery based on image and thermography data, focusing on motors and electrical panels. Enhance the operational stability of the machine through multimodal data fusion analysis using Convolutional Neural Networks (CNN). The model includes four parts: data collection, data preprocessing, and anomaly detection model training and deployment.

Source: Frontiers in artificial intelligence and applications

DOI: 10.3233/faia250114

Authors: Ting-Yi Chiang, I-long Lin

Institution: Tatung University

Language: English

Topic: Thermography and Photoacoustic Techniques

Subfield: Mechanics of Materials

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

OpenAlex ID: W4408335167

FWCI:

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