Toward cognitive predictive maintenance: A survey of graph-based approaches
Abstract Predictive Maintenance (PdM) has continually attracted interest from the
manufacturing community due to its significant potential in reducing unexpected machine …
manufacturing community due to its significant potential in reducing unexpected machine …
Residual-hypergraph convolution network: A model-based and data-driven integrated approach for fault diagnosis in complex equipment
Timely and accurate fault diagnosis plays a critical role in today's smart manufacturing
practices, saving invaluable time and expenditure on maintenance process. To date …
practices, saving invaluable time and expenditure on maintenance process. To date …
Graph cardinality preserved attention network for fault diagnosis of induction motor under varying speed and load condition
During the long-term operation of motors, their working conditions are changing due to the
industrial demands or declining health status, and traditional diagnosis methods perform …
industrial demands or declining health status, and traditional diagnosis methods perform …
ANOMALY DETECTION IN THE TEMPERATURE OF AN AC MOTOR USING EMBEDDED MACHINE LEARNING
The integration of machine learning solutions is becoming more prominent in the industry. In
industrial maintenance, new approaches categorized under predictive maintenance …
industrial maintenance, new approaches categorized under predictive maintenance …
GCPAT-Based Fault Diagnosis Method for Asynchronous Motors
X Dong, H **e, W Yanlei, C Hongwei… - … and Safety (ICRMS), 2023 - ieeexplore.ieee.org
In this paper, a fault diagnosis method based on GCPAT is proposed. Firstly, the vibration
signal is converted into a symmetrical snowflake image. Firstly, the vibration signal is …
signal is converted into a symmetrical snowflake image. Firstly, the vibration signal is …