17 papers with code • 0 benchmarks • 0 datasets
How do we know if communication is emerging in a multi-agent system?
To maximize the network s life, the proposed method, Centralized Naïve Bayes Detector (CNBD) analyzes the end-to-end transmission time collected at the sink.
Since PCA-based methods assume that the monitored process is linear, nonlinear PCA models, such as autoencoder models and kernel principal component analysis (KPCA), has been proposed and applied to nonlinear process monitoring.
630 RPM to 2330 RPM, three sensors were used to record vibrations on the rotating shaft at a sampling rate of 4096 values per second.
Distinguishing between classes of time series sampled from dynamic systems is a common challenge in systems and control engineering, for example in the context of health monitoring, fault detection, and quality control.
With the advancement of huge data generation and data handling capability, Machine Learning and Probabilistic modelling enables an immense opportunity to employ predictive analytics platform in high security critical industries namely data centers, electricity grids, utilities, airport etc.
In this work, we analyze vibration signal data of mechanical systems with bearings by combining different signal processing methods and coupling them with machine learning techniques to classify different types of bearing faults.