Search Results - "Shisheng ZHONG"

Genetic algorithm optimized double-reservoir echo state network for multi-regime time series prediction by Zhong, Shisheng, Xie, Xiaolong, Lin, Lin, Wang, Fang

“…In prognostics and health management (PHM), the sensor measurement time series of equipment is collected, and predicting future sensor measurements accurately…”
Get full text

A Weakly Supervised Gas-Path Anomaly Detection Method for Civil Aero-Engines Based on Mapping Relationship Mining of Gas-Path Parameters and Improved Density Peak Clustering by Sun, Hao, Fu, Xuyun, Zhong, Shisheng

“…Gas-path anomalies account for more than 90% of all civil aero-engine anomalies. It is essential to develop accurate gas-path anomaly detection methods…”
Get full text

A Newton method with characteristic value correction for geometric error calibration of parallel mechanism by Guo, Xiangyu, Wang, Rui, Zhao, Minghang, Zhong, Shisheng

“…To address the ill-conditioning of the Jacobian matrix in the geometric error calibration of parallel mechanisms, a Newton method with characteristic value…”
Get full text

Decision rule mining for machining method chains based on rough set theory by Wang, Rui, Guo, Xiangyu, Zhong, Shisheng, Peng, Gaolei, Wang, Lin

“…Decision rules for machining method chains mined from historical machining documents can help technologists quickly design new machining method chains…”
Get full text

Match performance of football teams in different competition phases: Analysis on the data of eight consecutive seasons in the Chinese Super League by Li, Pei, Zhong, Shisheng, Chmura, Paweł, Liu, Hongyou

“…The study aims to quantify the variation in the physical and technical match performance of football teams in different months of a season in the Chinese Super…”
Get full text

Trans-layer model learning: A hierarchical modeling strategy for real-time reliability evaluation of complex systems by Tan, Zhixue, Zhong, Shisheng, Lin, Lin

“…•Accurate estimation of component loading conditions in complex systems for life prediction model performance improvement.•Insights of components states for…”
Get full text

Adaptive Levenberg–Marquardt Algorithm: A New Optimization Strategy for Levenberg–Marquardt Neural Networks by Yan, Zhiqi, Zhong, Shisheng, Lin, Lin, Cui, Zhiquan

“…Engineering data are often highly nonlinear and contain high-frequency noise, so the Levenberg–Marquardt (LM) algorithm may not converge when a neural network…”
Get full text

Double-sided collaborative machining for propeller blade based on XYZ-3RPS hybrid kinematic machine by Guo, Xiangyu, Wang, Rui, Zhong, Shisheng

“…At present, propeller blades are machined single-sided with low efficiency. Thus, a propeller needs to be turned over after completion of the machining of the…”
Get full text

Collision avoidance and orientation planning for ball-end cutter by Guo, Xiangyu, Wang, Rui, Zhong, Shisheng

“…Propeller blades have freeform surfaces, and the overlap among the blades limits the adjustment range of cutter orientation, making it extremely difficult to…”
Get full text

A Novel Denoising Method for Retaining Data Characteristics Brought from Washing Aeroengines by Yan, Zhiqi, Zu, Ming, Cui, Zhiquan, Zhong, Shisheng

“…Airlines evaluate the energy-saving and emission reduction effect of washing aeroengines by analyzing the exhaust gas temperature margin (EGTM) data of…”
Get full text

Typical process discovery based on affinity propagation by Lin WANG, Yongjian ZHANG, Shisheng ZHONG

“…A lot of repeated work existed in the design of manufacturing process for similar parts, and many kinds of process knowledge which were not reused effectively…”
Get full text

A Study on the Generalized Approximation Modeling Method Based on Fitting Sensitivity for Prediction of Engine Performance by Lin, Lin, Zhong, Shisheng, Wang, Fang

“…Prediction technology for aeroengine performance is significantly important in operational maintenance and safety engineering. In the prediction of engine…”
Get full text

Deep Residual Shrinkage Networks for Fault Diagnosis by Zhao, Minghang, Zhong, Shisheng, Fu, Xuyun, Tang, Baoping, Pecht, Michael

“…This article develops new deep learning methods, namely, deep residual shrinkage networks, to improve the feature learning ability from highly noised vibration…”
Get full text

A Novel Time-Series Memory Auto-Encoder With Sequentially Updated Reconstructions for Remaining Useful Life Prediction by Fu, Song, Zhong, Shisheng, Lin, Lin, Zhao, Minghang

“…One of the significant tasks in remaining useful life (RUL) prediction is to find a good health indicator (HI) that can effectively represent the degradation…”
Get full text

Deep Residual Networks With Adaptively Parametric Rectifier Linear Units for Fault Diagnosis by Zhao, Minghang, Zhong, Shisheng, Fu, Xuyun, Tang, Baoping, Dong, Shaojiang, Pecht, Michael

“…Vibration signals under the same health state often have large differences due to changes in operating conditions. Likewise, the differences among vibration…”
Get full text

Random forests-based extreme learning machine ensemble for multi-regime time series prediction by Lin, Lin, Wang, Fang, Xie, Xiaolong, Zhong, Shisheng

“…•The random forests-based extreme learning machine ensemble model is proposed.•The model can be accurate, stable and efficient in time series prediction.•The…”
Get full text

Empirical mode reconstruction: Preserving intrinsic components in data augmentation for intelligent fault diagnosis of civil aviation hydraulic pumps by Meng, Linghui, Zhao, Minghang, Cui, Zhiquan, Zhang, Xingming, Zhong, Shisheng

“…•This paper develops empirical mode reconstruction to augment faulty samples.•Empirical mode reconstruction can preserve intrinsic components in the original…”
Get full text

Data Augmentation via Randomized Wavelet Expansion and Its Application in Few-Shot Fault Diagnosis of Aviation Hydraulic Pumps by Zhao, Minghang, Fu, Xuyun, Zhang, Yongjian, Meng, Linghui, Zhong, Shisheng

“…In general, deep learning-based fault diagnosis methods need a large number of training samples, which are often not available in real applications. Aiming at…”
Get full text

Gas turbine engine gas path anomaly detection using deep learning with Gaussian distribution by Hui Luo, Shisheng Zhong

“…Gas turbine engine anomaly detection is a critical means to ensure the safety and economic efficiency of a flight. As gas path faults make up a sizeable…”
Get full text

A re-optimized deep auto-encoder for gas turbine unsupervised anomaly detection by Fu, Song, Zhong, Shisheng, Lin, Lin, Zhao, Minghang

“…The use of hidden features or reconstruction errors extracted by deep auto-encoder (DAE) is becoming popular to discriminate anomalies from normal…”
Get full text