[PDF][PDF] A survey of predictive maintenance: Systems, purposes and approaches
This paper provides a comprehensive literature review on Predictive Maintenance (PdM)
with emphasis on system architectures, purposes and approaches. In industry, any outages …
with emphasis on system architectures, purposes and approaches. In industry, any outages …
Applications of artificial neural network based battery management systems: A literature review
Lithium-ion batteries have gained significant prominence in various industries due to their
high energy density compared to other battery technologies. This has led to their …
high energy density compared to other battery technologies. This has led to their …
Modified deep autoencoder driven by multisource parameters for fault transfer prognosis of aeroengine
The existing fault prognosis techniques of aeroengine mostly focus on a single monitoring
parameter under stable condition, and have low adaptability to new prognosis scenes. To …
parameter under stable condition, and have low adaptability to new prognosis scenes. To …
Tool condition monitoring for high-performance machining systems—A review
In the era of the “Industry 4.0” revolution, self-adjusting and unmanned machining systems
have gained considerable interest in high-value manufacturing industries to cope with the …
have gained considerable interest in high-value manufacturing industries to cope with the …
An ensemble framework based on convolutional bi-directional LSTM with multiple time windows for remaining useful life estimation
Effectively estimating remaining useful life (RUL) is crucially important for evaluating
machine health. In the industry, there exists a high degree of inconsistency among the …
machine health. In the industry, there exists a high degree of inconsistency among the …
Remaining useful life prognosis based on ensemble long short-term memory neural network
Remaining useful life (RUL) prognosis is of great significance to improve the reliability,
availability, and maintenance cost of an industrial equipment. Traditional machine learning …
availability, and maintenance cost of an industrial equipment. Traditional machine learning …
A survey on data-driven predictive maintenance for the railway industry
In the last few years, many works have addressed Predictive Maintenance (PdM) by the use
of Machine Learning (ML) and Deep Learning (DL) solutions, especially the latter. The …
of Machine Learning (ML) and Deep Learning (DL) solutions, especially the latter. The …
Aircraft engines remaining useful life prediction with an adaptive denoising online sequential extreme learning machine
Abstract Remaining Useful Life (RUL) prediction for aircraft engines based on the available
run-to-failure measurements of similar systems becomes more prevalent in Prognostic …
run-to-failure measurements of similar systems becomes more prevalent in Prognostic …
[HTML][HTML] Enabling predictive maintenance integrated production scheduling by operation-specific health prognostics with generative deep learning
Abstract Predictive Maintenance (PdM) is one of the core innovations in recent years that
sparks interest in both research and industry. While researchers develop more and more …
sparks interest in both research and industry. While researchers develop more and more …
Fault detection with LSTM-based variational autoencoder for maritime components
Maintenance routines on ships today follow either a reactive maintenance (RM) or
preventive maintenance (PvM) approach. RM can be regarded as post-failure repair, which …
preventive maintenance (PvM) approach. RM can be regarded as post-failure repair, which …