Rotating machinery is important to industrial production. Any failure of rotating machinery, especially the failure of rolling bearings, can lead to equipment shutdown and even more serious incidents. Therefore, accur...
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Rotating machinery is important to industrial production. Any failure of rotating machinery, especially the failure of rolling bearings, can lead to equipment shutdown and even more serious incidents. Therefore, accurate residual life prediction plays a crucial role in guaranteeing machine operation safety and reliability and reducing maintenance cost. In order to increase the forecasting precision of the remaining useful life(RUL) of the rolling bearing, an advanced approach combining elastic net with long short-time memory network(LSTM) is proposed, and the new approach is referred to as E-LSTM. The E-LSTM algorithm consists of an elastic mesh and LSTM, taking temporal-spatial correlation into consideration to forecast the RUL through the LSTM. To solve the over-fitting problem of the LSTM neural network during the training process, the elastic net based regularization term is introduced to the LSTM *** this way, the change of the output can be well characterized to express the bearing degradation mode. Experimental results from the real-world data demonstrate that the proposed E-LSTM method can obtain higher stability and relevant values that are useful for the RUL forecasting of bearing. Furthermore, these results also indicate that E-LSTM can achieve better performance.
The scope of this book is to present the papers included at the 21st UK Workshop on Computational Intelligence (UKCI 2022), hosted by The University of Sheffield, between 7 and 9 September 2022, Sheffield, UK. This ma...
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ISBN:
(数字)9783031555688
ISBN:
(纸本)9783031555671
The scope of this book is to present the papers included at the 21st UK Workshop on Computational Intelligence (UKCI 2022), hosted by The University of Sheffield, between 7 and 9 September 2022, Sheffield, UK. This marks the first fully in-person UKCI conference, following the pandemic, a testament to the success and resilience of the UKCI community, as well as to the importance of computational intelligence (CI) research. The papers in this book are divided into five sections: fuzzy logic systems, machine learning, hybrid methods and network systems, deep learning and neural networks, and optimization and search.
作者：
Grzedzinski, KacperTrodden, PaulRolls-Royce Control
Monitoring and Systems Engineering University Technology Centre Department of Automatic Control and Systems Engineering University of Sheffield United Kingdom
The dual-control problem of simultaneously regulating a plant and identifying its dynamics is addressed in a linear model predictive control (MPC) framework. We propose and study an approach where two optimal control ...
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In this paper, a simple and effective PI controller tuning method is presented. To take both performance requirements and robustness issues into consideration, the design technique is based on optimization of load dis...
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This work describes a novel method for the reduction of SISO continuous models. The proposed method, the least squares Pade (LS-Pade) method, provides reduced models which incorporate some information about the origin...
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This work describes a novel method for the reduction of SISO continuous models. The proposed method, the least squares Pade (LS-Pade) method, provides reduced models which incorporate some information about the original model over the mid-frequency range. Consequently, the present method gives better results than the classical Pade and most of the related methods for a very small additional cost.
In this paper Principal Components Analysis (PCA) is used for detecting faults in a simulated wastewater treatment plant (WWTP). Diagnosis tasks are treated using Fisher discriminant analysis (FDA). Both techniques ar...
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ISBN:
(纸本)9783902661548
In this paper Principal Components Analysis (PCA) is used for detecting faults in a simulated wastewater treatment plant (WWTP). Diagnosis tasks are treated using Fisher discriminant analysis (FDA). Both techniques are multivariate statistical techniques used in multivariate statistical process control (MSPC) and fault detection and isolation (FDI) perspectives. PCA reduces the dimensionality of the original historical data by projecting it onto a lower dimensionality space. It obtains the principal causes of variability in a process. If some of these causes change, it can be due to a fault in the process. FDA provides an optimal lower dimensional representation in terms of a discriminant between classes of data, where, in this context of fault diagnosis, each class corresponds to data collected during a specific and known fault. A discriminant function is applied to diagnose faults using data collected from the plant.
Technologies that providemechanical assistance arerequired inthemdicalfeld,such asimplants that regenerate tssuethroughelongation and *** ofthe challenges is to develop actuators that combinethe benefits ofhigh axiale...
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Technologies that providemechanical assistance arerequired inthemdicalfeld,such asimplants that regenerate tssuethroughelongation and *** ofthe challenges is to develop actuators that combinethe benefits ofhigh axialextension at lowpressures,modularity,multifunction,and load bearing capabilities into one design while maintaining their shape and *** such a challenge wll provide implants with enhanced capacity for mechanical assistance to induce *** introduce two novel actuators(M2H)built of stacked Hyperelastic Balloning Membrane Actuators(HBMAs)that can be realized using helical and toroidal *** restraining the HBMA expansion deterministicallyusing a semisoft exoskeleton,the actuatorsors areendoweded withh axial extension and radial expansion *** actuatorsare thus built of modules that canconfiguured different therapeutical needs and multifunctionality,to provideanatomically congruent *** desigl,fabricationtestin;and numerical and experimental validation ofthe *** can aaxiallyind6 in their helicaland toroidal configurations at input pressuresas low as 26 and 24 kPa,*** the axial module is used separately,its extension capacity reaches>170%.The M2H-HBMAs can perform independent and simultaneousxpansion and extension motions with negligible intraluminaldeformation as well as stand at least 1kg of axial force without *** M2H-HBMAs overcome the limitations ofhyperexpanding machines that show low resistance to *** envisage M2H-HBMAs as promising tools to perform tisueregeneration procedures.
In this paper Principal Components Analysis (PCA) is used for detecting faults in a plant with multiple operation modes. PCA reduces the dimensionality of the original historical data by projecting it onto a lower dim...
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Metamaterials have recently received significant interest in several fields. They provide the ability to construct materials with unique physical characteristics. This notably includes materials with a negative refrac...
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ISBN:
(纸本)9781617823961
Metamaterials have recently received significant interest in several fields. They provide the ability to construct materials with unique physical characteristics. This notably includes materials with a negative refractive index, the implications of which are wave refraction in the opposite direction to the conventional sense during propagation between mediums with opposite signed refractive indices. Most of the developments for pressure waves are limited to fluid borne noise in a frequency regime determined by their physical construction. This paper presents methods which allow solid viscoelastic metamaterials with controllable properties to be constructed. It is shown how it is possible to construct materials which have both a negative effective density and elasticity in a desired frequency zone. These methods provide a notable step towards the practical realization of some of the proposed novel applications of metamaterials.
This paper presents the development of a symbolic approach in characterising the dynamic behaviour of flexible robot manipulators using finite element (FE) methods. A constrained planar single link flexible manipulato...
This paper presents the development of a symbolic approach in characterising the dynamic behaviour of flexible robot manipulators using finite element (FE) methods. A constrained planar single link flexible manipulator is considered. A simulation algorithm of the system is developed using a symbolic language which enables system characterisation with varying parameters. Analyses and investigations in terms of system transfer function, stability, response and endpoint vibration to an input command are presented. An assessment of the performance of the approach is presented and discussed through numerical simulations.
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