With the implementation of 14th Five-Year Plan in China and the completion of the poverty
alleviation task, the economy in China has made great progress. However, the carbon …

In alarm systems, conventional univariate alarm methods often result in frequent false and
missing alarms, calling for an urgent need to introduce multivariate information. For the …

In harsh climates, highway icing poses a hazard to traffic safety and increases road
maintenance costs. It is of great significance to predict when the highway icing may occur …

Multimode processes are common in modern industry and refer to processes that work in
multiple operating modes. Motivated by the torque control process of a wind turbine, we …

Clustering algorithms and deep learning methods have been widely applied in the
multimode process monitoring. However, for the process data with unknown mode …

To improve the accuracy of feature representation and abnormal condition identification, a
new abnormal condition identification method, named integrating multiple binary neural …

Detecting defects on surfaces is a crucial challenge in the steel industry. Various object
detection models, including one-stage and two-stage approaches, have been developed to …

Anomaly detection in manufacturing systems is challenging, because anomalies are rarely
generated. Additionally, Radiography Testing (RT) data for welds are difficult to share …

This paper proposes the method for cleaning up label noise in multivariate time-series
outlier data. An image plotting method is proposed to reflect the tendency of original time …