Junyu Guo
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View article: A risk-based review of dangerous goods storage and handling at a manufacturing facility
A risk-based review of dangerous goods storage and handling at a manufacturing facility Open
The safe storage and handling of dangerous goods (DGs) remain critical to preventing accidents, protecting personnel, and ensuring regulatory compliance within industrial manufacturing facilities. This paper examines the storage practices …
View article: Uncertainty-aware hourly load forecasting of hydrogen-blended natural gas with a hybrid deep learning model
Uncertainty-aware hourly load forecasting of hydrogen-blended natural gas with a hybrid deep learning model Open
View article: Data-Driven Prediction of Metal Fatigue Life
Data-Driven Prediction of Metal Fatigue Life Open
With the rapid development of additive manufacturing (AM) technology, its applications in aerospace, medical, and automotive industries are becoming increasingly widespread. This paper investigates the fatigue life prediction of additively…
View article: A Parallel Prognostic Method Integrating Uncertainty Quantification for Probabilistic Remaining Useful Life Prediction of Aero-Engine
A Parallel Prognostic Method Integrating Uncertainty Quantification for Probabilistic Remaining Useful Life Prediction of Aero-Engine Open
Remaining useful life (RUL) prediction plays a fundamental role in the prognostics and health management of mechanical equipment. Consequently, extensive research has been devoted to estimating the RUL of mechanical equipment. Owing to the…
View article: Data-Driven Feature Extraction-Transformer: A Hybrid Fault Diagnosis Scheme Utilizing Acoustic Emission Signals
Data-Driven Feature Extraction-Transformer: A Hybrid Fault Diagnosis Scheme Utilizing Acoustic Emission Signals Open
This paper introduces a novel network, DDFE-Transformer (Data-Driven Feature Extraction-Transformer), for fault diagnosis using acoustic emission signals. The DDFE-Transformer network integrates two primary modules: the DDFE module, focusi…
View article: A hybrid deep learning model towards fault diagnosis of drilling pump
A hybrid deep learning model towards fault diagnosis of drilling pump Open
This paper proposes a novel method namely WaveletKernelNet-Convolutional Block Attention Module-BiLSTM for intelligent fault diagnosis of drilling pumps. Initially, the random forest method is applied to determine the target signals that c…
View article: A parallel deep neural network for intelligent fault diagnosis of drilling pumps
A parallel deep neural network for intelligent fault diagnosis of drilling pumps Open
This paper introduces a novel parallel deep neural network for fault diagnosis of drilling pumps. It integrates the Convolutional Block Attention Module with the AlexNet and synchronizes with the Anomaly Transformer model to delve meticulo…
View article: A hybrid prognosis scheme for rolling bearings based on a novel health indicator and nonlinear Wiener process
A hybrid prognosis scheme for rolling bearings based on a novel health indicator and nonlinear Wiener process Open
This paper proposes a novel hybrid method aiming at the fault prognosis of bearings. A nonlinear health indicator is first constructed using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Kernel Principal Component …
View article: Bayesian Fusion of Degradation and Failure Time Data for Reliability Assessment of Industrial Equipment Considering Individual Differences
Bayesian Fusion of Degradation and Failure Time Data for Reliability Assessment of Industrial Equipment Considering Individual Differences Open
In the field of industrial equipment reliability assessment, dependency on either degradation or failure time data is common. However, practical applications often reveal that single-type reliability data for certain industrial equipment a…
View article: Numerical Analysis of Heat Transfer Performance of Liquefied Natural Gas Intermediate Fluid Vaporizer
Numerical Analysis of Heat Transfer Performance of Liquefied Natural Gas Intermediate Fluid Vaporizer Open
View article: A deep learning based health indicator construction and fault prognosis with uncertainty quantification for rolling bearings
A deep learning based health indicator construction and fault prognosis with uncertainty quantification for rolling bearings Open
In this paper, a hybrid convolutional neural network (CNN)-bidirectional gated recurrent unit (BiGRU) model is integrated with the bootstrap method to endow the deep learning (DL) based prognostic method with the quantification capability …
View article: A hybrid intelligent rolling bearing fault diagnosis method combining WKN-BiLSTM and attention mechanism
A hybrid intelligent rolling bearing fault diagnosis method combining WKN-BiLSTM and attention mechanism Open
Fault diagnosis of rolling bearings helps ensure mechanical systems’ safety. The characteristics of temporal and interleaved noise in the bearing fault diagnosis data collected in the industrial field are addressed. This paper proposes a h…
View article: Harmonic contribution determination based on change‐point monitoring and shape context algorithm
Harmonic contribution determination based on change‐point monitoring and shape context algorithm Open
In the power system, the harmonic is one of the important concerns of power quality, which has a significant impact on the safe operation of power grids and the energy efficiency for users. When there are not enough special harmonic monito…
View article: A Method for Responsibility Division of Multi-Harmonic Sources Based on Canonical Correlation Analysis
A Method for Responsibility Division of Multi-Harmonic Sources Based on Canonical Correlation Analysis Open
The variable background harmonic data and incomplete phasor information make multi-harmonic source responsibility division in three-phase symmetrical power system a significant challenge. In this paper, a background harmonic data selection…
View article: Study on the Damage Model of Coal Rock Caused by Hydraulic Pressure and Electrical Impulse in Borehole
Study on the Damage Model of Coal Rock Caused by Hydraulic Pressure and Electrical Impulse in Borehole Open
The purpose of this study is to study the damage and fracturing effects of high-voltage discharge on coal-rock mass under the action of hydrostatic pressure. Based on the traditional damage evolution model and the change of the effective b…
View article: A Convergence-Accelerated Distributed Time Synchronization Algorithm for Energy-Harvesting Wireless Sensor Networks
A Convergence-Accelerated Distributed Time Synchronization Algorithm for Energy-Harvesting Wireless Sensor Networks Open
Time synchronization is an essential problem for energy-harvesting wireless sensor networks (EH-WSNs), which is closely related to efficient resource schedules, energy harvesting, data fusion, location, etc. With the advantage of being mor…
View article: RLCard: A Platform for Reinforcement Learning in Card Games
RLCard: A Platform for Reinforcement Learning in Card Games Open
We present RLCard, a Python platform for reinforcement learning research and development in card games. RLCard supports various card environments and several baseline algorithms with unified easy-to-use interfaces, aiming at bridging reinf…
View article: RLCard: A Toolkit for Reinforcement Learning in Card Games
RLCard: A Toolkit for Reinforcement Learning in Card Games Open
RLCard is an open-source toolkit for reinforcement learning research in card games. It supports various card environments with easy-to-use interfaces, including Blackjack, Leduc Hold'em, Texas Hold'em, UNO, Dou Dizhu and Mahjong. The goal …
View article: Insulin-like growth factor-1 inhibits the apoptosis of rat gastric smooth muscle cells cultured under high glucose condition through PI3K-Akt-PKC-Ca<sup>2+</sup>pathway
Insulin-like growth factor-1 inhibits the apoptosis of rat gastric smooth muscle cells cultured under high glucose condition through PI3K-Akt-PKC-Ca<sup>2+</sup>pathway Open
This study investigated the effect of insulin-like growth factor 1 (IGF-1) on rat gastric smooth muscle cell apoptosis under high glucose conditions, and explored the involvement of the PI3K-Akt-PKC-Ca2+ pathway. Rat gastric smooth muscle …
View article: A Bayesian Approach for Degradation Analysis with Individual Differences
A Bayesian Approach for Degradation Analysis with Individual Differences Open
Reliability assessments of long-life and high-reliability products often face the difficulty of lack of failure time data. Meanwhile, there existing individual differences in produces due to the uncertainties during their whole lifetime, s…
View article: Bayesian Hierarchical Model-Based Information Fusion for Degradation Analysis Considering Non-Competing Relationship
Bayesian Hierarchical Model-Based Information Fusion for Degradation Analysis Considering Non-Competing Relationship Open
Degradation analysis methods are increasingly used in reliability assessment of long-life products. The small sample size problem is worthy of attention in the degradation analysis. Bayesian hierarchical method is employed for fusing multi…
View article: Effect of Slice Error of Glass on Zero Offset of Capacitive Accelerometer
Effect of Slice Error of Glass on Zero Offset of Capacitive Accelerometer Open
Packaging process had been studied on capacitance accelerometer. The silicon-glass bonding process had been adopted on sensor chip and glass, and sensor chip and glass was adhered on ceramic substrate, the three-layer structure was curved …
View article: LDA Meets Word2Vec
LDA Meets Word2Vec Open
Clustering narrow-domain short texts, such as academic abstracts, is an extremely difficult clustering problem. Firstly, short texts lead to low frequency and sparseness of words, making clustering results highly unstable and inaccurate; S…
View article: Use of Quantitative Dynamic Contrast-Enhanced Ultrasound to Assess Response to Antiangiogenic Therapy in Children and Adolescents With Solid Malignancies: A Pilot Study
Use of Quantitative Dynamic Contrast-Enhanced Ultrasound to Assess Response to Antiangiogenic Therapy in Children and Adolescents With Solid Malignancies: A Pilot Study Open
Contrast-enhanced ultrasound measurements of tumor peak enhancement, rate of enhancement, and AUC1 were early predictors of time to progression in a cohort of children and adolescents with recurrent solid tumors treated with antiangiogenic…