With the rapid advancement of sensor and network technology, there has been a notable
increase in the availability of condition-monitoring data such as vibration, temperature …

Industrial process data is complex time series data including trend and periodicity. However,
the existing soft sensor models only focus on the time series context. Therefore, a novel …

Bridge construction is one of the cores of traffic infrastructure construction. To better develop
relevant bridge science, this paper introduces the main research progress in China and …

The heat exchanger (HE) is an important component of almost every energy generation
system. Periodic inspection of the HEs is particularly important to keep high efficiency of the …

Since labelled data are expensive to generate both computationally and experimentally,
how to establish data-driven models with limited data has become an important challenge in …

For aeroengine multitask prognosis, dataset's quantity and quality significantly affect the
prediction performance. Due to the insufficiency and high redundancy of collected data, data …

Drift compensation is an important issue for metal oxide semiconductor (MOS) gas sensor
arrays. General machine learning methods require constant calibration and a large amount …

The increasing interest for adopting electromechanical actuators (EMAs) on aircraft
demands improved diagnostic and prognostic methodologies to be applied to such systems …

Calibration is the backbone of any sensor and measurement philosophy. The conventional
calibration techniques for electrical parameter measurement using nonlinear sensors are …

Health state prediction and fault time prediction are two key tasks in the fault prediction field.
However, existing fault prediction techniques perform these tasks hierarchically and …