fault diagnosis

Multimodal Fault Diagnosis Using 1D-GRU and 2D-MTF-ResNet-CBAM

by
Multimodal Fault Diagnosis Using 1D-GRU and 2D-MTF-ResNet-CBAM

IntroductionThis issue introduces a multimodal fusion classification model based on 1D-GRU+2D-MTF-ResNet-CBAM, which has shown remarkable results in fault diagnosis tasks!1 Model Overview and Innovations1.1 Model OverviewThis model combines time-frequency images and one-dimensional time series signals, utilizing a ResNet optimized with the CBAM attention mechanism and a GRU multimodal feature fusion model for fault signal classification. … Read more

AI-Powered Precision Diagnosis of Dementia

by
AI-Powered Precision Diagnosis of Dementia

Introduction Differential diagnosis of dementia has always been a challenge in neurology. Due to the overlap of symptoms from various causes, this process is particularly complex. However, accurate differential diagnosis is crucial for developing early personalized treatment strategies. On July 4th, Nature Medicine reported “AI-based differential diagnosis of dementia etiologies on multimodal data“ which introduced … Read more

Quantitative Abnormality Diagnosis Method for Power Batteries Based on 1D CNN-LSTM

by
Quantitative Abnormality Diagnosis Method for Power Batteries Based on 1D CNN-LSTM

In the 2024 issue 7 of “Automobile Engineering”, the research results from the School of Mechanical and Automotive Engineering at South China University of Technology were published: “A Quantitative Diagnosis Method for Power Battery Faults Based on 1D CNN-LSTM Considering Cell Abnormalities”. The paper combines three types of features: the vehicle’s motion state, the drive … Read more

Rolling Bearing Fault Diagnosis Method Based on NLF-LSTM

by
Rolling Bearing Fault Diagnosis Method Based on NLF-LSTM

Peng Cheng 1，2，Jiang Jinyuan 1，Li Fengjuan 1 （1.Hunan University of Technology, School of Computer Science, Zhuzhou, Hunan 412007； 2.Central South University, School of Automation, Changsha, Hunan 410083） Abstract: This paper addresses the difficulty of hyperparameter configuration in fault diagnosis using deep learning methods. To effectively optimize the set of hyperparameters, we propose an optimization algorithm … Read more

Classification of Gastrointestinal Dysfunction (AGI)

by
Classification of Gastrointestinal Dysfunction (AGI)

According to the severity of gastrointestinal dysfunction, gastrointestinal dysfunction (AGI) can be classified into four levels, each corresponding to different treatment measures: AGI Level I: There is a clear etiology leading to temporary partial gastrointestinal dysfunction, manifested as temporary and self-limiting, with the risk of gastrointestinal dysfunction and failure. For example: nausea and/or vomiting occurring … Read more

Applications of Knowledge Graphs in the Industrial Sector

by
Applications of Knowledge Graphs in the Industrial Sector

A knowledge graph is a technology for organizing and representing knowledge in a graph structure, which builds a computable and inferable knowledge base by abstracting entities, attributes, and relationships. The graphical data structure allows machines to process and understand complex information more naturally, making data retrieval and analysis more efficient. In recent years, knowledge graphs … Read more