51 citations · 109 across the 8 of their papers we have counts for
8 papers
Assessing Covariate-Informed Grid Load Forecasting with a Time-Series Foundation Model
Varsha Pendyala, Yiwei Fu, Weizhong Yan +1
Modern power systems are growing increasingly complex as they integrate diverse generation sources to meet rising demand, making accurate load forecasting challenging. Recent advan…
One Masked Model is All You Need for Sensor Fault Detection, Isolation and Accommodation
Yiwei Fu, Weizhong Yan
Accurate and reliable sensor measurements are critical for ensuring the safety and longevity of complex engineering systems such as wind turbines. In this paper, we propose a novel…
Multivariate Time Series Anomaly Detection with Few Positive Samples
Feng Xue, Weizhong Yan
Given the scarcity of anomalies in real-world applications, the majority of literature has been focusing on modeling normality. The learned representations enable anomaly detection…
On Adversarial Vulnerability of PHM algorithms: An Initial Study
Weizhong Yan, Zhaoyuan Yang, Jianwei Qiu
With proliferation of deep learning (DL) applications in diverse domains, vulnerability of DL models to adversarial attacks has become an increasingly interesting research topic in…
On Accurate and Reliable Anomaly Detection for Gas Turbine Combustors: A Deep Learning Approach
Weizhong Yan, Lijie Yu
Monitoring gas turbine combustors health, in particular, early detecting abnormal behaviors and incipient faults, is critical in ensuring gas turbines operating efficiently and in…
Power Plant Performance Modeling with Concept Drift
Rui Xu, Yunwen Xu, Weizhong Yan
Power plant is a complex and nonstationary system for which the traditional machine learning modeling approaches fall short of expectations. The ensemble-based online learning meth…
Concept Drift Learning with Alternating Learners
Yunwen Xu, Rui Xu, Weizhong Yan +1
Data-driven predictive analytics are in use today across a number of industrial applications, but further integration is hindered by the requirement of similarity among model train…
Time Series Classification from Scratch with Deep Neural Networks: A Strong Baseline
Zhiguang Wang, Weizhong Yan, Tim Oates
We propose a simple but strong baseline for time series classification from scratch with deep neural networks. Our proposed baseline models are pure end-to-end without any heavy pr…