Hongquan Ji

发表

Optimization-Based Incipient Fault Isolation for the High-Speed Train Air Brake System

Hongquan Ji, 2022, IEEE Transactions on Instrumentation and Measurement.

A hybrid feature model and deep learning based fault diagnosis for unmanned aerial vehicle sensors

Yang Liu, Rui Yang, Maiying Zhong, 2018, Neurocomputing.

Improved multiclass support vector data description for planetary gearbox fault diagnosis

Hongquan Ji, Hui Hou, Hongquan Ji, 2021 .

Incipient fault detection of the high-speed train air brake system with a combined index

Donghua Zhou, Hongquan Ji, Donghua Zhou, 2020 .

Smoothed Fisher Discriminant Analysis for Incipient Fault Diagnosis

Zhiwen Chen, Youqing Wang, Hongquan Ji, 2018, IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society.

Recursive transformed component statistical analysis for incipient fault detection

Donghua Zhou, Jun Shang, Mao-Yin Chen, 2017, Autom..

Incipient fault detection with smoothing techniques in statistical process monitoring

Donghua Zhou, Jun Shang, Xiao He, 2017 .

On the use of reconstruction-based contribution for fault diagnosis

Donghua Zhou, Xiao He, Hongquan Ji, 2016 .

Incipient sensor fault isolation based on augmented Mahalanobis distance

Donghua Zhou, Keke Huang, Hongquan Ji, 2019, Control Engineering Practice.

I T ] 1 0 N ov 2 02 0 Detection of Intermittent Faults Based on an Optimally Weighted Moving Average T 2 Control Chart with Stationary Observations

M. Pecht, Xiao He, Donghua Zhou, 2020 .

Detection of Intermittent Faults Based on an Optimally Weighted Moving Average T^2 Control Chart with Stationary Gaussian Observations

Donghua Zhou, Hongquan Ji, Yinghong Zhao, 2020, Autom..

Statistics Mahalanobis distance for incipient sensor fault detection and diagnosis

Hongquan Ji, Hongquan Ji, 2021 .

Incipient sensor fault diagnosis in multimode processes using conditionally independent Bayesian learning based recursive transformed component statistical analysis

Donghua Zhou, Jun Shang, Maoyin Chen, 2019, Journal of Process Control.

Multimode process monitoring based on robust dictionary learning with application to aluminium electrolysis process

Cheng Long, Chunhua Yang, Keke Huang, 2019, Neurocomputing.

Isolating incipient sensor fault based on recursive transformed component statistical analysis

Donghua Zhou, Jun Shang, Hongquan Ji, 2018 .

Nonlinear process monitoring using kernel dictionary learning with application to aluminum electrolysis process

Chunhua Yang, Keke Huang, Cen Lihui, 2019, Control Engineering Practice.

Determining the optimal kernel parameter in KPCA based on sample reconstruction

Donghua Zhou, Gang Li, Xiao He, 2016, CCC 2016.

Diagnosis of sensor precision degradation using Kullback‐Leibler divergence

Donghua Zhou, Xiao He, Hongquan Ji, 2018 .

Recursive Correlative Statistical Analysis Method With Sliding Windows for Incipient Fault Detection

Hongquan Ji, Yayun Yan, Yihao Qin, 2021, IEEE Transactions on Industrial Electronics.

Fault Detection and Isolation of the Brake Cylinder System for Electric Multiple Units

Donghua Zhou, Jun Shang, Xiao He, 2018, IEEE Transactions on Control Systems Technology.

Generalized grouped contributions for hierarchical fault diagnosis with group Lasso

Dexian Huang, Xiaolin Huang, Fan Yang, 2019 .

Dominant trend based logistic regression for fault diagnosis in nonstationary processes

Donghua Zhou, Jun Shang, Haifeng Zhang, 2017 .

Adaptive process monitoring via online dictionary learning and its industrial application.

Chunhua Yang, Cheng Long, Bei Sun, 2020, ISA transactions.

Determining the optimal kernel parameter in KPCA based on sample reconstruction

Zhou Donghua, He Xiao, Ji Hongquan, 2016, 2016 35th Chinese Control Conference (CCC).