The rapid development of photovoltaic (PV) technology and the growing number and size of
PV power plants require increasingly efficient and intelligent health monitoring strategies to …

This paper presents a comprehensive overview of modelling, simulation and implementation
of neural networks, taking into account that two aims have emerged in this area: the …

Sensitive feature extraction from the raw vibration signal is still a great challenge for
intelligent fault diagnosis of rolling bearing. Current fault classification framework generally …

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 …

Intelligent fault diagnosis of rotating machinery is essentially a pattern recognition problem.
Meanwhile, effective feature extraction from the raw vibration signal is an important …

The progress of machine learning (ML) in the past years has opened up new opportunities
to the field of gas turbine (GT) modelling. However, successful implementation of ML …

Bayesian network (BN) is a commonly used tool in probabilistic reasoning of uncertainty in
industrial processes, but it requires modeling of large and complex systems, in situations …

Automated ultrasonic signal classification systems are finding increasing use in many
applications for the recognition of large volumes of inspection signals. Wavelet transform is a …

Accurate service-life prediction of structures is vital for taking appropriate measures in a time-
and cost-effective manner. However, the conventional prediction models rely on simplified …

Deep learning is characterized by strong self-learning and fault classification ability without
manually feature extraction stage of traditional algorithms. Deep belief network (DBN) is one …