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A Novel Channel Pruning Lightweight Pig Face Detection Method Based on Augment Group Diverse Attention Mechanism
Shuiqing Xu;Wenhao Yi;Juan Shen;Songbing Tao;Hai Wang;Yi Chai;Hongtian Chen
Pig face detection plays a pivotal role in the intelligent management of pig farms. This study proposes a novel lightweight pig face detection model, named channel pruning pig face detection method based on augment group diverse attention mechanism (CPADA). First, to overcome the adverse effects of pig face smudges occlusion and significant intraclass variations on the detection performance, this ...Show More
A Lightweight Pig Face Recognition Method Based on Efficient Mobile Network and Horizontal Vertical Attention Mechanism
Shuiqing Xu;Haodong Zheng;Songbing Tao;Yi Chai;Qihang He;Hongtian Chen
Pig face recognition is a crucial tool in preventing and controlling swine fever, as well as optimizing pig farming practices. This study proposes an end-to-end lightweight pig face recognition method called EHV-YOLO, which can accurately identify pig faces from multiple angles and detect faces covered with dirt or external objects. First, to enhance the effectiveness of pig face feature extractio...Show More
Fault Estimation for Nonlinear Systems with Time Delay Based on Iterative Learning Scheme
2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
In this paper, the problem of fault estimation for a class of nonlinear systems with time delay is studied. First, an iterative learning observer and an exponential function-based fault estimation law are designed to improve the accuracy of fault estimation results. Then, we use the λ-norm method to derive the convergence conditions for the proposed fault estimator and provide the corresponding pr...Show More
Pig Face Recognition Based on Trapezoid Normalized Pixel Difference Feature and Trimmed Mean Attention Mechanism
Shuiqing Xu;Qihang He;Songbing Tao;Hongtian Chen;Yi Chai;Weixing Zheng
Pig face recognition has a wide range of applications in breeding farms, including precision feeding and disease surveillance. This article proposes a method to guarantee its performance in complex environments such as with dirty faces and in unconstrained outdoor conditions. First, inspired by the shape of the pig face, a trapezoid normalized pixel difference (T-NPD) feature is designed to achiev...Show More
Multiple Open-Circuit Fault Diagnosis for Back-to-Back Converter of PMSG Wind Generation System Based on Instantaneous Amplitude Estimation
Shuiqing Xu;Songbing Tao;Weixing Zheng;Yi Chai;Mingyao Ma;Lijian Ding
To increase the reliability and availability of wind turbines, a new diagnosis method was proposed for multiple open-circuit faults in the back-to-back converters of turbines using permanent magnet synchronous generators (PMSGs). This method is the first to use the instantaneous amplitude (IA) as the principal quantity for formulating diagnostic variables that can distinguish different states of a...Show More
Online Open-Circuit Fault Detection and Location utilizing Estimated Instantaneous Amplitudes
2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)
Year: 2019 | Conference Paper |
Cited by: Papers (1)
As one of the most key parts of wind power generation systems (WPGSs), the grid-connected converter plays a significant role for energy conversion. It is meaningful to ensure the stability and safety of converters in WPGSs. In this paper, a novel signal processing based approach is proposed to detect and locate power switch failures in grid-connected converters of WPGSs, which is completely differ...Show More
Wind power scenarios have a significant impact on stochastic optimization problems for power systems in which wind power is a significant component. Generative adversarial networks (GANs) are a powerful class of generative models, and can generate realistic scenarios for renewable power sources without the need for any modeling assumptions. However, the performance of GANs in generating scenarios ...Show More
The moving window principal component analysis (MWPCA) technique has been widely applied for dynamic statistical process monitoring of multivariate processes. To deal with abnormal situations with small fault symptoms, in our previous work, a novel incipient fault diagnosis method based on the Kullback-Leibler divergence (KLD) has been developed. Although certain algorithms have been given to sele...Show More
Affected by nonlinear and non-stationary problems, classical linear analysis approaches may fail in analyzing real-world signals, such as the biomedical data. As a fully data-driven and unsupervised signal analysis algorithm, the empirical mode decomposition (EMD) has been developed and applied widely in various fields, especially for de-noising filtering. Due to the increasing need of high speed ...Show More
Incipient fault online estimation based on Kullback-Leibler Divergence and fast moving window PCA
IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
Year: 2017 | Conference Paper |
Cited by: Papers (4)
The realization of early detection of incipient faults makes great sense for the guarantee of system performance and security operation. Therefore, It is necessary to estimate the fault amplitude especially when the system security assessment is the main goal. Regarding the incipient fault with low Fault-Noise-ratio (FNR), in this paper, a practical online fault estimation method is presented for ...Show More
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