Zhinong Jiang
Orcid: 0000-0003-3844-5905Affiliations:
- Beijing University of Chemical Technology, China
According to our database1,
Zhinong Jiang
authored at least 14 papers
between 2011 and 2022.
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Bibliography
2022
Decoupling Identification Method of Continuous Working Conditions of Diesel Engines Based on a Graph Self-Attention Network.
IEEE Access, 2022
2021
Erratum to "Local Maximum Synchrosqueezing Chirplet Transform: An Effective Tool for Strongly Nonstationary Signals of Gas Turbine".
IEEE Trans. Instrum. Meas., 2021
Local Maximum Synchrosqueezing Chirplet Transform: An Effective Tool for Strongly Nonstationary Signals of Gas Turbine.
IEEE Trans. Instrum. Meas., 2021
Bearing Condition Evaluation Based on the Shock Pulse Method and Principal Resonance Analysis.
IEEE Trans. Instrum. Meas., 2021
Multi-Type Diesel Engines Operating Condition Recognition Method Based on Stacked Auto-Encoder and Feature Transfer Learning.
IEEE Access, 2021
2020
A Variational Stacked Autoencoder with Harmony Search Optimizer for Valve Train Fault Diagnosis of Diesel Engine.
Sensors, 2020
Bearing State Recognition Method Based on Transfer Learning Under Different Working Conditions.
Sensors, 2020
An Intelligent Fault Diagnosis Scheme Using Transferred Samples for Intershaft Bearings Under Variable Working Conditions.
IEEE Access, 2020
2019
A New Fault Diagnosis Method for a Diesel Engine Based on an Optimized Vibration Mel Frequency under Multiple Operation Conditions.
Sensors, 2019
Multi-Factor Operating Condition Recognition Using 1D Convolutional Long Short-Term Network.
Sensors, 2019
2018
Proceedings of the 2018 IEEE International Conference on Prognostics and Health Management, 2018
Lithium-ion battery state of charge estimation based on dynamic neural network and Kalman filter.
Proceedings of the 2018 IEEE International Conference on Prognostics and Health Management, 2018
2017
Fault Diagnosis of Internal Combustion Engine Valve Clearance Using the Impact Commencement Detection Method.
Sensors, 2017
2011
A recognition and novelty detection approach based on Curvelet transform, nonlinear PCA and SVM with application to indicator diagram diagnosis.
Expert Syst. Appl., 2011