Software fault prediction using data mining, machine learning and deep learning techniques: A systematic literature review
Software fault/defect prediction assists software developers to identify faulty constructs, such
as modules or classes, early in the software development life cycle. There are data mining …
as modules or classes, early in the software development life cycle. There are data mining …
Recent advances in sensor fault diagnosis: A review
As an essential component of data acquisition systems, sensors have been widely used,
especially in industrial and agricultural sectors. However, sensors are also prone to faults …
especially in industrial and agricultural sectors. However, sensors are also prone to faults …
Data-driven methods for predictive maintenance of industrial equipment: A survey
W Zhang, D Yang, H Wang - IEEE systems journal, 2019 - ieeexplore.ieee.org
With the tremendous revival of artificial intelligence, predictive maintenance (PdM) based on
data-driven methods has become the most effective solution to address smart manufacturing …
data-driven methods has become the most effective solution to address smart manufacturing …
Deep convolutional neural network model based chemical process fault diagnosis
H Wu, J Zhao - Computers & chemical engineering, 2018 - Elsevier
Numerous accidents in chemical processes have caused emergency shutdowns, property
losses, casualties and/or environmental disruptions in the chemical process industry. Fault …
losses, casualties and/or environmental disruptions in the chemical process industry. Fault …
Anomaly detection using autoencoders in high performance computing systems
Anomaly detection in supercomputers is a very difficult problem due to the big scale of the
systems and the high number of components. The current state of the art for automated …
systems and the high number of components. The current state of the art for automated …
[PDF][PDF] 基于数据驱动的微小故障诊断方法综述
文成林， 吕菲亚， 包哲静， 刘妹琴 - 自动化学报, 2016 - aas.net.cn
摘要能否及时诊断出微小故障是保障系统安全运行并抑制故障恶化的关键,
本文针对微小故障幅值低, 易被系统扰动和噪声掩盖等特点, 从数据驱动的角度对现有研究进行 …
本文针对微小故障幅值低, 易被系统扰动和噪声掩盖等特点, 从数据驱动的角度对现有研究进行 …
Process topology convolutional network model for chemical process fault diagnosis
D Wu, J Zhao - Process Safety and Environmental Protection, 2021 - Elsevier
There always exists potential safety risk in chemical processes. Abnormalities or faults of the
processes can lead to severe accidents with unexpected loss of life and property. Early and …
processes can lead to severe accidents with unexpected loss of life and property. Early and …
Deep learning-based fault diagnosis of photovoltaic systems: A comprehensive review and enhancement prospects
Photovoltaic (PV) systems are subject to failures during their operation due to the aging
effects and external/environmental conditions. These faults may affect the different system …
effects and external/environmental conditions. These faults may affect the different system …
One step forward for smart chemical process fault detection and diagnosis
X Bi, R Qin, D Wu, S Zheng, J Zhao - Computers & Chemical Engineering, 2022 - Elsevier
Process fault detection and diagnosis (FDD) is an essential tool to ensure safe production in
chemical industries. After decades of development, despite the promising performance of …
chemical industries. After decades of development, despite the promising performance of …
Fault detection and classification using artificial neural networks
Process monitoring is considered to be one of the most important problems in process
systems engineering, which can be benefited significantly from deep learning techniques. In …
systems engineering, which can be benefited significantly from deep learning techniques. In …