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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Niu, Chaoyue Chen, Bin Smith, Erica Bramley, Robert Crawforth, Pete Mahfouf, Mahdi Kadirkamanathan, Visakan The Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3JD United Kingdom The Advanced Manufacturing Research Centre with Boeing University of Sheffield RotherhamS60 5TZ United Kingdom

ISBN: (纸本)9798331527471

Aircraft assembly entails drilling numerous holes, often in multi-material stacks, then joining parts with fasteners fitted through the holes. There are stringent quality requirements on the holes, and assessment of hole quality is crucial to ensuring the integrity of the joints. Carbon fibre reinforced polymer (CFRP) is a commonly used material in aircraft structures due to its desirable properties. However, it is susceptible to defects not associated with metals, such as delamination and uncut fibres. While there have been multiple metrics for assessment of these defects proposed in literature, relatively few attempts to consolidate them have been seen. Furthermore, common measurement methods used for assessing these defects (e.g. 3D-microscopy) are well established, but can be time-consuming;manual interrogation of raw inspection data can also be highly subjective. To address these challenges, this paper proposes a set of combined metrics along with an automatic image processing framework for fast assessment of delamination and uncut fibre defects. The combined metric for the delamination region is aggregated from across six factors and uncut fibre uniform metrics from across five factors. The image processing framework receives grayscale images as inputs, taken from an optical coordinate measuring machine, and outputs the combined metrics along with eleven separate metrics. Experimental results, using a preexisting dataset from twenty-four holes on two workpieces from a real robotic drilling operation, are given to demonstrate the effectiveness of the proposed combined metrics and the corresponding image processing framework. © 2024 IEEE.

关键词： Carbon fiber reinforced plastics

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An Adaptive CUSUM Approach for Automating Sleep Apnoea Analysis Based on Pulse and Oximetry Data 20

An Adaptive CUSUM Approach for Automating Sleep Apnoea Analy...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Yang, Dongjin Bhargava, Eishaan Elphick, Heather Mihaylova, Lyudmila S. University of Sheffield Dept. of Automatic Control and Systems Engineering United Kingdom Sheffield Children's Hospital Department of Paediatric Otolaryngology Sheffield United Kingdom Sheffield Children's Hospital Department of Paediatric Respiratory and Sleep Medicine Sheffield United Kingdom

ISBN: (纸本)9798350320831

Sleep apnoea is a common sleep disorder during human sleep. It is usually diagnosed by a doctor after recording one nights' sleep signals. Patients have to go to the hospital to record sleep signals, which is time-consuming and resource-intensive. The study focused on two signals, pulse data and oximetry data, with the aim of detecting apnoea using a single signal. This paper introduced an anomaly detection approach using the adaptive cumulative sum (ACUSUM) change point detection algorithm to monitor outliers in the signal. In addition, the test results of ACUSUM will be compared with the test results of classical CUSUM. Besides, the threshold selection has been changed from an unchanging constant to a value related to the standard deviation of the selected signal based on a rational subgroup process. The results of the comparison confirm that ACUSUM is better than classical CUSUM in the accuracy of automatic detection. © 2023 IEEE.

关键词： Anomaly detection

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Out-of-distribution Object Detection through Bayesian Uncertainty Estimation 26

Out-of-distribution Object Detection through Bayesian Uncert...

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26th International Conference on Information Fusion, FUSION 2023

作者： Zhang, Tianhao Wang, Shenglin Bouaynaya, Nidhal Calinescu, Radu Mihaylova, Lyudmila The University of Sheffield Automatic Control and Systems Engineering United Kingdom Rowan University Department of Electrical and Computer Engineering United States University of York Department of Computer Science United Kingdom

ISBN: (纸本)9798890344854

The superior performance of object detectors is often established under the condition that the test samples are in the same distribution as the training data. However, in many practical applications, out-of-distribution (OOD) instances are inevitable and usually lead to uncertainty in the results. In this paper, we propose a novel, intuitive, and scalable probabilistic object detection method for OOD detection. Unlike other uncertainty-modeling methods that either require huge computational costs to infer the weight distributions or rely on model training through synthetic outlier data, our method is able to distinguish between in-distribution (ID) data and OOD data via weight parameter sampling from proposed Gaussian distributions based on pre-trained networks. We demonstrate that our Bayesian object detector can achieve satisfactory OOD identification performance by reducing the FPR95 score by up to 8.19% and increasing the AUROC score by up to 13.94% when trained on BDD100k and VOC datasets as the ID datasets and evaluated on COCO2017 dataset as the OOD dataset. © 2023 International Society of Information Fusion.

关键词： Object detection

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Utilization of Uniform Circular Array for Estimating RF Source Location in Real-time

Utilization of Uniform Circular Array for Estimating RF Sour...

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International Conference on control, Automation and Diagnosis (ICCAD)

作者： Hamad Alsayegh Mohammad Almuhaihi Automatic Control and Systems Engineering Department University of Sheffield Aerospace Engineering Department University of Michigan

ISBN: (数字)9798350361025

ISBN: (纸本)9798350361032

This Radio Frequency (RF) source location estimation scheme utilizes angles of arrival of a signal source acquired from the Multiple Signal Classification (MUSIC) algorithm. In reliance on that as a Maximum Likelihood estimation, the obtained angles are augmented to an adaptive probability distribution function (PDF), which is then employed to estimate the location of the RF emitter by feeding the PDF to an Extended Kalman Filter (EKF). Numerous use cases and theoretical works have been presented in the literature. Some of these papers mention applications regarding implementing DoA algorithms in dynamic platforms like in [9], [10], [11], [12], and [13] mostly all of them use Uniform Linear Array (ULA), four of them working with Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), and one with MUSIC Direction of Arrival (DoA) method. In [14], MUSIC was used with a Uniform Circular Array (UCA). However, less coupling has been incorporated with the covariance of measurement error. In this paper, the dynamic 2D DoA MUSIC algorithm used in a platform, applied together with an EKF estimation and coupled with measurement covariance in a simulation environment to precisely locate an RF emitter and provide high-resolution Line-of-Sight (LOS).

关键词： Radio frequency Maximum likelihood estimation Direction-of-arrival estimation Heuristic algorithms Current measurement Estimation Position measurement

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Identification of Thermal Failure Profiles in Stator Winding Insulation by Impedance Spectroscopy

Identification of Thermal Failure Profiles in Stator Winding...

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2024 International Conference on Electrical Machines, ICEM 2024

作者： Stone, Edward J. W. Panagiotou, Panagiotis A. Muhlthaler, Johannes Mills, Andrew R. Lambourne, Alexis Jewell, Geraint W. The University of Sheffield Department of Electronic and Electrical Engineering Sheffield United Kingdom Rolls-Royce Electrical Rolls-Royce Deutschland Ltd & Co KG Munich Germany The University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom Rolls-Royce Central Services Rolls-Royce Plc. UK Derby United Kingdom

ISBN: (纸本)9798350370607

This paper presents a novel application of impedance spectroscopy as a means of inspection for stator winding insulation. It proposes, for the first time, a means for health monitoring and failure identification during thermal degradation effects in the insulation systems of stator coils from a concentrated stator winding. By periodical ex-situ inspection of these coils, the thermal ageing data of the insulation are profiled up to the point of failure. The study maps this evolution of thermal degradation patterns via novel interpretation of the impedance frequency responses, using well known techniques such as the Bode and Nyquist plots. This grants further insight into the characteristics shown in the ageing profiles over time and frequency. These new profiles enable the identification of critical points that can act as pre-emptive indicators of coil health and failure inception. This is a key finding as it renders the capability to provide an adequate lifing tool for electrical machine windings and coil assemblies within industrial settings. The insulation system examined in this study is taken from the coils of a concentrated stator winding in a 2MW permanent magnet generator used in an aerospace application. © 2024 IEEE.

关键词： Stators

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Modelling of Insulation in Concentrated Stator Coils for Characterisation and Material Changes

Modelling of Insulation in Concentrated Stator Coils for Cha...

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2024 International Conference on Electrical Machines, ICEM 2024

作者： Stone, Edward J. W. Panagiotou, Panagiotis A. Muhlthaler, Johannes Mills, Andrew R. Lambourne, Alexis Jewell, Geraint W. The University of Sheffield Department of Electronic and Electrical Engineering Sheffield United Kingdom Rolls-Royce Deutschland Ltd & Co KG Rolls-Royce Electrical Munich Germany The University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom Rolls-Royce Plc. UK Rolls-Royce Central Services Derby United Kingdom

ISBN: (纸本)9798350370607

The highly demanding operation of electrical machines in aerospace can lead to the degradation of electrical insulation systems within the machine windings over time. This paper presents a novel method for high frequency modelling of a coil from the concentrated stator winding of an 2MW aerospace generator, for the purpose of characterising the insulation system by the amplitude and phase responses by the Bode plots in the same framework as electrical impedance spectroscopy. This new approach of high frequency model utilises a finite element model, deployed in tandem with an electrical equivalent circuit representation. Matlab is used to quantify the results taken from finite element modelling and implemented into LTSpice, so that the model considers mutual coupling of inductances and high-frequency effects, such as proximity and skin effects. This novel methodology allows extraction of the impedance profile with respect to the material changes within the simulated insulation system. © 2024 IEEE.

关键词： MATLAB

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Narrow gap TIG arc weld process monitoring 27

Narrow gap TIG arc weld process monitoring

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27th International Conference on Automation and Computing, ICAC 2022

作者： Gambrill, Nathan Farnsworth, Michael Shaw, Rob Tedeschi, Stefano Tiwari, Divya Tiwari, Ashutosh The University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom The Welding Institute Ltd Abington Cambridge United Kingdom

ISBN: (数字)9781665498074

ISBN: (纸本)9781665498074

Joining processes play a critical role across several industries and manufacturing activities. One such activity is narrow gap TIG arc welding, present in a number of high value manufacturing domains the quality and outcomes are highly dependent on the operating parameters and the evolving state of the weld. Human supervision, and the application of vision systems to allow the operator to monitor the process as it is being undertaken is commonplace, however monitoring, characterisation and feedback in narrow gap use cases is less so. The work undertakes a comparative study into two different approaches to process monitoring of TIG arc welding. The first through more traditional machine vision (MV) methods, and the second through more modern deep neural network methods. Results show both methods developed are able to perform the role of process monitoring and defect detection with accuracy of 82% and 93% for the traditional and DNN methods respectively. © 2022 IEEE.

关键词： Deep neural networks

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Environment-Modulated Self-Assembly by Changes in Modules’ Buoyancy

Environment-Modulated Self-Assembly by Changes in Modules’ ...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Xiao Chen Junyi Han Xin Jin Shuhei Miyashita Automatic Control and Systems Engineering Department University of Sheffield Sheffield UK Insigneo Institute for in Silico Medicine

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

While many inkjet printers employ only four types of ink (i.e. CKMY) to produce a wide range of colors, numerous technical challenges still exist for contemporary 3D printers to fabricate various materials and generate composite products such as electric devices. Conversely, there have been attempts and endeavors to make things through self-assembly of parts, analogous to the autonomous and decentralized development process of the human body from just 20 types of amino acids. In our previous work, we proposed a method for the rapid production of 3D objects using the centimeter-sized modules (referred to as Roblets) capable of generating a 2D structure and subsequently self-folding themselves into a 3D configuration, akin to origami. To further leverage the capability of generating a wide variety of different types of structures by combining different modules, this research studies a method of automatically selecting and supplying modules using environmental cues. More precisely, we developed a mechanism to couple different modules corresponding to three different environments (on a flat surface, on low-dense saline, and on saturated saline) and yielded different module configurations. The process of self-assembly necessitated the application of perturbation, which was realized by imparting magnetic torque originating from an external magnetic field onto the magnets embedded in the modules.

关键词： Self-assembly Three-dimensional displays Torque Buoyancy Production Magnetic fields Printers

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Uncertainty-Informed Model Selection Method for Nonlinear System Identification and Interpretable Machine Learning 32

Uncertainty-Informed Model Selection Method for Nonlinear Sy...

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32nd Mediterranean Conference on control and Automation, MED 2024

作者： Gu, Yuanlin Wei, Hua-Liang University of Stirling Division of Computer Science and Maths StirlingFK9 4LA United Kingdom University of Sheffield Department of Automatic Control and Systems Engineering SheffieldS1 3JD United Kingdom

ISBN: (纸本)9798350395440

Modeling uncertainty has been an active and important topic in the fields of data-driven modeling and machine learning. Uncertainty ubiquitously exists in any data modeling process, making it challenging to identify the optimal models among many potential candidates. This article proposes an uncertainty-informed method to address the model selection problem. The performance of the proposed method is evaluated on a dataset generated from a complex system model. The experimental results demonstrate the effectiveness of the proposed method and its superiority over conventional approaches. This method has minimal requirements for the length of training data and model types, making it applicable for various modeling frameworks. © 2024 IEEE.

关键词： Machine learning

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LMI-based Decentralized Load Frequency control of a Hybrid Power System with a Virtual Synchronous Generator and Battery Storage

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IFAC-PapersOnLine 2023年第2期56卷 10910-10916页

作者： Abdulla Omaruddin Paul Trodden Nuclear & Power Atkins UK Department of Automatic Control and Systems Engineering The University of Sheffield UK

This paper proposes the participation of wind generation in the decentralized control of load frequency of a hybrid power system consisting of, in addition to wind generation, conventional generation and battery storage. The wind generation is modelled as a ‘Virtual Synchronous Generator (VSG)’ in a separate control area with its own virtual frequency. It has also been proposed to operate the wind generation system in a ‘de-loaded’ mode, thereby allowing it to take part in frequency regulation services. For the purposes of a decentralized control design, the overall system model is decomposed into three subsystems. Static state-feedback control gains are computed by posing the decentralized control problem as a set of linear matrix inequalities (LMIs) subject to structural and stabilizing constraints.

关键词： Optimal operation and control of power systems control of renewable energy resources control system design

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