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Found 3 papers, 2 papers with code
Adversarial Attacks and Defenses in Automated Control Systems: A Comprehensive Benchmark
By evaluating three neural networks with different architectures, we subject them to six types of adversarial attacks and explore five different defense methods.
Graph Neural Networks with Trainable Adjacency Matrices for Fault Diagnosis on Multivariate Sensor Data
In this work, the possibility of applying graph neural networks to the problem of fault diagnosis in a chemical process is studied.
SensorSCAN: Self-Supervised Learning and Deep Clustering for Fault Diagnosis in Chemical Processes
However, manual annotation of large amounts of data can be difficult in industrial settings.
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