다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

A most critical and important issue surrounding the design of automatic control systems with the successively increasing complexity is guaranteeing a high system performance over a wide operating range and meeting the requirements on system reliability and dependability. As one of the key technologies for the problem solutions, advanced fault detection and identification (FDI) technology is receiving considerable attention. The objective of this book is to introduce basic model-based FDI schemes, advanced analysis and design algorithms and the needed mathematical and control theory tools at a level for graduate students and researchers as well as for engineers.

Model-based Fault Diagnosis Techniques: Design Schemes, Algorithms, and Tools

With the continuous increase in complexity and expense of industrial systems, there is less tolerance for performance degradation, productivity decrease, and safety hazards, which greatly necessitates to detect and identify any kinds of potential abnormalities and faults as early as possible and implement real-time fault-tolerant operation for minimizing performance degradation and avoiding dangerous situations. During the last four decades, fruitful results have been reported about fault diagnosis and fault-tolerant control methods and their applications in a variety of engineering systems. The three-part survey paper aims to give a comprehensive review of real-time fault diagnosis and fault-tolerant control, with particular attention on the results reported in the last decade. In this paper, fault diagnosis approaches and their applications are comprehensively reviewed from model- and signal-based perspectives, respectively.

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A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches

Recently, to ensure the reliability and safety of modern large-scale industrial processes, data-driven methods have been receiving considerably increasing attention, particularly for the purpose of process monitoring. However, great challenges are also met under different real operating conditions by using the basic data-driven methods. In this paper, widely applied data-driven methodologies suggested in the literature for process monitoring and fault diagnosis are surveyed from the application point of view. The major task of this paper is to sketch a basic data-driven design framework with necessary modifications under various industrial operating conditions, aiming to offer a reference for industrial process monitoring on large-scale industrial processes.

A Review on Basic Data-Driven Approaches for Industrial Process Monitoring

The electric vehicle (EV) is targeted as an efficient method of decreasing CO2 emission and reducing dependence on fossil fuel. Compared with filling up the internal combustion engine (ICE) vehicle, the EV power charging time is usually long. However, to the best of our knowledge, the current charging strategy does not consider the battery state of health (SOH). It is noted that a high charging current rate may damage the battery life. Motivated by this, an optimal charging strategy is proposed in the present paper, providing several optimal charging options taking into account the EV battery health, trying to prevent `abused battery utilization' happening.

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Optimal charging strategy for EVs with batteries at different states of health

This paper presents a quantitative review of early detection and estimation of fault for wind turbine system The model-based technique is proposed to provide an assessment of all possible faults for renewable energy sources The augmented observer is applied to estimate the real physical data of the system sensor faults and states simultaneously The fault detection and diagnosis is designed to be most sensitive to faults and states of wind turbine system A mathematical example is specified to exhibit the dynamic system behavior for the wind turbine model to validate the competence of the system performance The state space is used to explain the design The satisfactory fault diagnosis performance is demonstrated in the simulation results

Simulation Study of Fault Detection and Diagnosis for Wind Turbine System

This is the second part of our series works on failure-informed adaptive sampling for physic-informed neural networks (FI-PINNs). In our previous work \cite{gao2022failure}, we have presented an adaptive sampling framework by using the failure probability as the posterior error indicator, where the truncated Gaussian model has been adopted for estimating the indicator. In this work, we present two novel extensions to FI-PINNs. The first extension consist in combining with a re-sampling technique, so that the new algorithm can maintain a constant training size. This is achieved through a cosine-annealing, which gradually transforms the sampling of collocation points from uniform to adaptive via training progress. The second extension is to present the subset simulation algorithm as the posterior model (instead of the truncated Gaussian model) for estimating the error indicator, which can more effectively estimate the failure probability and generate new effective training points in the failure region. We investigate the performance of the new approach using several challenging problems, and numerical experiments demonstrate a significant improvement over the original algorithm.

Failure-informed adaptive sampling for PINNs, Part II: combining with re-sampling and subset simulation

In this paper, a concise two-state clock model is proposed to describe the behaviour of drifting internal oscillator clocks with non-identical and time-varying frequencies, which provides a simple analytical solution of different coupling schemes’ effects on synchronisation performance. The improved Pulse-Coupled Oscillators (PCO) scheme presented in this paper guarantees the synchronisation on non-identical and time-varying clocks. Meanwhile, it differs from classical PCO by scheduling the transmission of Syncs (i.e., the Pulses of clock) at different time slots. This collision-free pulse coupling scheme makes the concept of PCO applicable to wireless sensor networks, as it is practically impossible in realistic wireless networks for multiple oscillators to transmit Pulses at the same time. Furthermore, a proportional controller is adopted to correct the clock, and convergence and stability of the proposed algorithm are theoretically analysed, proved and evaluated by hardware experiments. The experimental results show that the improved PCO scheme can achieve synchronisation with the precision of around 400 µs on internal oscillator clocks of about 350, 000 ppm.

Experimental Evaluation of Non-identical Pulse-Coupled Oscillators Synchronisation in IEEE 802.15.4 Wireless Sensor Networks

This paper investigates robust fault estimation and fault tolerant control problems for stochastic Lipschitz nonlinear systems subject to Brownian motions, unexpected faults and unknown inputs. Augmented system approach and unknown input observer are integrated to produce robust estimates of the means of the faults and the full system states simultaneously. Based on the well-designed fault estimation scheme, a robust fault tolerant control strategy is proposed to compensate faults, stabilize the closed loop system, and eliminate the effects of unknown inputs. Sufficient conditions are presented in terms of linear matrix inequalities for the overall closed-loop system composed of both states and error dynamics to guarantee the stability and robustness of the system. Furthermore, the systematic design procedure for the robust fault estimation and fault tolerant control scheme is addressed. Finally, simulation on a single joint robotic model is illustrated to validate the suggested methodologies.

Zhiwei Gao

Papers

Optimal charging strategy for EVs with batteries at different states of health

Simulation Study of Fault Detection and Diagnosis for Wind Turbine System

Failure-informed adaptive sampling for PINNs, Part II: combining with re-sampling and subset simulation

Experimental Evaluation of Non-identical Pulse-Coupled Oscillators Synchronisation in IEEE 802.15.4 Wireless Sensor Networks

Robust fault estimation and fault tolerant control for Lipschitz nonlinear brownian systems