In modern plants, industrial processes typically operate under different states to meet the different requirements of high-quality products. Many monitoring models for industrial processes were ...constructed based on the prior knowledge (the mechanism's model or the process data characteristics) to monitor such processes (called multimode processes). However, obtaining this prior knowledge is difficult in practice. Efficiently monitoring nonlinear multimode processes without any prior knowledge is an open problem that demands further exploration. Since data from different modes follow different distributions while data from the same mode are considered to be sampled from the same distribution, the modes of multimode processes can be uncovered based on the characteristics of the process data. This article proposes using a Dirichlet process Gaussian mixed model to classify the modes of multimode processes based on historical data, and then, determine the mode types of the monitored data. A nonlinear monitoring strategy based on the t-distributed stochastic neighbor embedding is then proposed to achieve nonlinear dimensionality reduction and visualize the data. Finally, a monitoring index that is integrated with support vector data description is constructed for comprehensive monitoring. The proposed nonlinear multimode framework completely realizes data-driven mode identification and unsupervised fault detection without knowing any prior knowledge. The effectiveness and feasibility of the proposed model are demonstrated using data from a simulated wastewater treatment plant.
Abstract
Environmental perturbations and noise are source of mode mixing and interferences between the propagating modes of a complex multi-mode fiber (MMF). Typically, they are characterized by ...their correlation (paraxial) length, and their spectral content which describes the degree of coupling between various modes. We show that an appropriate control of these quantities allows to engineer Levy-type relaxation processes of an initial mode excitation. Our theory, based on random matrix theory modeling, is tested against realistic simulations with MMFs.
Multivariate statistical process monitoring (MSPM) methods are powerful tools for detecting faults in industrial systems. However, industrial processes are often subjected to dynamic changes. This ...dynamic behavior is mainly due to set-point changes and nonlinearities. Because of the nonlinearity of processes, the performance of the classical MSPM methods, which are mainly based on the linearity assumption, becomes unsatisfactory, since the process characteristics will change from one operating point to another. The main objective of the work is to develop an efficient fault detection technique for complex industrial systems, using process historical data and considering the nonlinear behavior of the process. In the proposed approach, the nonlinear system is assumed to be linear around the operating points and therefore considered as a piecewise linear system corresponding to each operating mode. The performance and effectiveness of this approach are demonstrated using data obtained from a paper machine and compared with an available method.
Input and command shapers are great open-loop control strategies in reducing residual vibration in rest-to-rest maneuvers. The generation of such command usually contains multiple impulses and jerks. ...Multiple impulses usually degrade the performance due to actuation delay and mismatch timing while jerks reduce the life expectancy of actuator and increase maintenance. In this work, a smooth single multimode command shaping control is proposed and tested numerically and experimentally to eliminate residual vibration in rest-to-rest maneuvers. The advantages of the technique are summarized as, the proposed technique has an adjustable maneuvering time, can eliminate all vibration modes regardless of the number, the required parameters are found analytically which eliminate the need of complex or lengthy calculation needed for most multimode shaper, smooth command profile to eliminate jerks i.e. inrush current, and it is continuous with single actuation to eliminate inaccurate timing and delay. The technique performance is validated numerically and experimentally. Numerical simulations prove that the shaped commands are capable of completely eliminating residual vibrations of multimode systems. Furthermore, the proposed technique is utilized to reduce the sensitivity of the shaper to modeling errors. Unlike other shaper the proposed reduction in the sensitivity can be implemented for all modes with no added complexity.
Engine test beds are widely used to estimate automotive engine parameters and design controllers in the preliminary development phase. The controller parameters are optimized to fulfill emission, ...fuel consumption and driving comfort requirements and they will be further validated on chassis dynamometer and road driving experiments. It is common that the results of two experiments deviate, due to some external disturbances or faults. The main purpose of this paper is to demonstrate the application of data-driven fault diagnosis techniques to detect the deviations in the experiments and analyze their root-causes to reduce the costs and time of the engine design and its control concept. To this end, two different methods are introduced for detection of the problems in the experiment. Based on the results of the detection step, a fault isolation technique has been proposed to support test engineers in finding the cause of the deviations. The results have been demonstrated on an industrial engine test bed and the effectiveness of the methods is discussed.
Rogue waves are giant waves appearing erratically and unexpectedly on the ocean surfaces. Their existence, considered as mythical in the ancient times, has recently been recognised by the scientific ...community and, since then, rogue waves have become the object of numerous theoretical and experimental studies. Their relevance is not restricted to oceanography, but it extends in a wide spectrum of physical contexts. General models and mathematical tools have been developed on a interdisciplinary ground and many experiments have been specifically conceived for the observation of rogue waves in a variety of different physical systems. Rogue wave phenomena are, nowadays, studied, for instance, in hydrodynamics, optics, plasmas, complex media, Bose-Einstein condensation and acoustics. We can, therefore, consider rogue waves as a paradigmatic description, able to account for the manifestation of extreme events in multidisciplinary physics. In this review, we present the main physical concepts and mathematical tools for the description of rogue waves. We will refer mostly to examples from water waves and optics, the two domains having in common the non-linear Schrödinger equation from which prototype rogue wave solutions can be derived. We will highlight the most common features of the rogue wave phenomena, as the large deviations from the Gaussian statistics of the amplitude, the existence of many uncorrelated 'grains' of activity and their clustering in inhomogeneous spatial domains via large-scale symmetry breaking.
Multi-mode embedded real-time systems exhibit a specific behaviour for each mode, and upon a mode-change request the task-set and timing interfaces of the system need to be changed. This paper ...presents the implementation of a MultiMode Adaptive Hierarchical Scheduling Framework (MMAHSF) and provides a generic skeleton (framework) for a two-level adaptive hierarchical scheduling supporting multiple modes and multiple mode-change mechanisms on an open source real-time operating system (FreeRTOS). The MMAHSF enable application-specific implementations of mode-change protocols using a set of predefined mode-change mechanisms. The paper addresses different mode-change mechanisms at both global and local scheduling levels. It presents examples of mode-change protocols that are developed by composing together these mechanisms in multiple ways and provide the initial results of executing these protocols in the MMAHSF implementation on an AVR 32-bit board EVK1100.
We present a novel co-design methodology for the synthesis of energy-efficient embedded systems. In particular, we concentrate on distributed embedded systems that accommodate several different ...applications within a single device, i.e., multimode embedded systems. Based on the key observation that operational modes are executed with different probabilities, that is, the system spends uneven amounts of time in the different modes, we develop a new co-design technique that exploits this property to significantly reduce energy dissipation. Energy and cost savings are achieved through a suitable synthesis process that yields better hardware-resource-sharing opportunities. We conduct several experiments, including a realistic smart phone example, that demonstrate the effectiveness of our approach. Reductions in power consumption of up to 64% are reported.
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