Forecasting the Dynamic Response of Rotating Machinery under Sudden Load Changes

Article Engineering, Aerospace

A Multilayered and Multifactorial Health Assessment Method for Launch Vehicle Engine under Vibration Conditions

Ruliang Lin et al.

Summary: This article proposes a multi-layer and multi-factor predictive evaluation method for a fuzzy and complex system in order to assess its health status. Experimental results show that this method can successfully predict and evaluate the engine system.

AEROSPACE (2023)

添加到收藏夹

Article Chemistry, Multidisciplinary

An Application of Instantaneous Spectral Entropy for the Condition Monitoring of Wind Turbines

Marco Civera et al.

Summary: This research proposes a method based on vibration detection and condition monitoring to alleviate operation and maintenance costs of wind turbines, and uses instantaneous spectral entropy and continuous wavelet transform for anomaly detection and fault diagnosis.

APPLIED SCIENCES-BASEL (2022)

添加到收藏夹

Article Computer Science, Information Systems

Prediction of Network Traffic in Wireless Mesh Networks Using Hybrid Deep Learning Model

Smita Mahajan et al.

Summary: Wireless mesh networks are widely adopted in network communication, and traffic prediction is crucial for accurately forecasting network traffic using historical data. This paper analyzes various traffic prediction methods, presents a case study predicting performance of a High-Speed Diesel pump, and introduces a novel Convo-LSTM model that outperforms other models in predicting pump performance.

IEEE ACCESS (2022)

添加到收藏夹

Article Automation & Control Systems

Incipient Fault Diagnosis for High-Speed Train Traction Systems via Stacked Generalization

Zehui Mao et al.

Summary: This article proposes a stacking-based incipient fault diagnosis scheme for the traction system of high-speed trains, using machine learning algorithms for fault feature extraction and classification. Experimental results demonstrate that the proposed method outperforms single model approaches.

IEEE TRANSACTIONS ON CYBERNETICS (2022)

添加到收藏夹

Review Energy & Fuels

Fault Diagnosis of Electric Motors Using Deep Learning Algorithms and Its Application: A Review

Yuanyuan Yang et al.

Summary: Recent research has shown that deep learning has better performance in fault detection of electric motors compared to traditional methods, due to its more powerful and sophisticated feature extraction capabilities. This paper covers four traditional types of deep learning models in detecting faults of electric motors and discusses the issues and prospects that deep learning encounters in the fault detection mechanism.

ENERGIES (2021)

添加到收藏夹

Article Multidisciplinary Sciences

Time series data analysis and ARIMA modeling to forecast the short-term trajectory of the acceleration of fatalities in Brazil caused by the corona virus (COVID-19)

Akini James et al.

Summary: This paper analyzes the fatalities caused by coronavirus in Brazil and predicts the trajectory of fatalities for the next six months using the concept of acceleration. The results show a general decrease in fatalities over the next six months, with a gradual slowing down of the pace.

PEERJ (2021)

添加到收藏夹

Article Chemistry, Multidisciplinary

Auto-Regressive Integrated Moving-Average Machine Learning for Damage Identification of Steel Frames

Yuqing Gao et al.

Summary: The study combines time series modeling and machine learning classification to propose an automated framework for damage feature extraction, successfully overcoming the limitations of non-stationarity, and demonstrating high accuracy and robustness in experimentation.

APPLIED SCIENCES-BASEL (2021)

添加到收藏夹

Article Chemistry, Analytical