With the ever increase of complexity and expense industrial systems, there is less tolerance for performance degradation, productivity decrease safety hazards, which greatly stimulates to detect identify any kinds potential abnormalities faults as early possible, implement realtime fault-tolerant operation minimizing degradation avoiding dangerous situations.During last four decades, fruitful results were reported about fault diagnosis control methods their applications in a variety...

This is the second-part paper of survey on fault diagnosis and fault-tolerant techniques, where methods applications are overviewed, respectively, from knowledge-based hybrid/active viewpoints. With aid first-part paper, review completes a whole overview techniques their applications. Comments advantages constraints various including model-based, signal-based, knowledge-based, also given. An overlook future development presented.

This review paper is to give a full picture of fault detection and diagnosis (FDD) in complex systems from the perspective data processing. As matter fact, an FDD system data-processing on basis information redundancy, which human's understanding are two fundamental elements. Human's may be explicit input–output model representing relationship among system's variables. It also represented as knowledge implicitly (e.g., connection weights neural network). Therefore, done through some kind...

Robust fault estimation plays an important role in real-time monitoring, diagnosis, and fault-tolerance control. Accordingly, this paper aims to develop effective technique simultaneously estimate the system states concerned faults, while minimizing influences from process/sensor disturbances. Specifically, augmented is constructed by forming state vector composed of faults. Next, unknown input observer (UIO) designed for decoupling partial disturbances attenuating that cannot be decoupled,...

This "Special Section on Real-Time Fault Diagnosis and Fault-Tolerant Control" of the IEEE Transactions Industrial Electronics is motivated to provide a forum for academic industrial communities report recent theoretic/application results in real-time monitoring, diagnosis, fault-tolerant design, exchange ideas about emerging research direction this field. Twenty-three papers were eventually selected through strict peer-reviewed procedure, which represent most progress fault control their...

Wind energy is contributing to more and portions in the world market. However, one deterrent even greater investment wind considerable failure rate of turbines. In particular, large turbines are expensive, with less tolerance for system performance degradations, unscheduled shut downs, damages caused by various malfunctions or faults occurring components such as rotor blades, hydraulic systems, generator, electronic control units, electric sensors, so forth. As a result, there high demand...

Privacy protection as a major concern of the industrial big data enabling entities makes massive safety-critical operation wind turbine unable to exert its great value because threat privacy leakage. How improve diagnostic accuracy decentralized machines without transfer remains an open issue; especially these are almost accompanied by skewed class distribution in real industries. In this study, class-imbalanced privacy-preserving federated learning framework for fault diagnosis is proposed....

.Physics-informed neural networks (PINNs) have emerged as an effective technique for solving PDEs in a wide range of domains. It is noticed, however, that the performance PINNs can vary dramatically with different sampling procedures. For instance, fixed set (prior chosen) training points may fail to capture solution region (especially problems singularities). To overcome this issue, we present work adaptive strategy, termed failure-informed (FI-PINNs), which inspired by viewpoint...

For descriptor systems with measurement output noises (input disturbances may exist at the same time), a new estimator technique is developed. The necessary and sufficient condition for existence of present derived, systematic design approach addressed. effect uncertainties decoupled completely, asymptotic estimates system state noise are obtained simultaneously. Furthermore, normal state/disturbance also given. class nonlinear both input uncertainties, derived by using proposed approach,...

In response to the high demand of operation reliability by implementing real-time monitoring and system health management, a robust fault estimation fault-tolerant control approach is proposed for Takagi-Sugeno fuzzy systems in this study, integrating augmented method, unknown input observer design, linear matrix inequality optimization, signal compensation techniques. Specifically, method used construct an plant with concerned faults states being states. An technique thus utilized estimate...

In this paper, a novel discrete-time estimator is proposed, which employed for simultaneous estimation of system states, and actuator/sensor faults in dynamic system. The existence the proven mathematically. systematic design procedure derivative proportional observer gains addressed, enabling error dynamics to be internally proper stable, robust against effects from process disturbances, measurement noise, faults. Based on estimated fault signals fault-tolerant approach by may recover...

A review of black-box models for short-term time-discrete prediction the silicon content hot metal produced in blast furnaces is presented. The primarily focused on work presented journal papers, but still includes some early conference papers (published before 1990) which have a clear contribution to field. Linear and nonlinear are treated separately, within each group rough subdivision according model type made. Within subsection (almost) chronologically, presenting principle behind...

In this paper, a robust fault estimation approach is proposed for multi-input and multioutput nonlinear dynamic systems on the basis of back propagation neural networks. The augmented system approach, input-to-state stability theory, linear matrix inequality optimization, network training/learning are integrated so that simultaneous estimate states actuator faults achieved. approaches finally applied to 4.8 MW wind turbine benchmark system, effectiveness well demonstrated.

In response to the high demand of operation reliability and predictive maintenance, health monitoring fault diagnosis classification have been paramount for complex industrial systems (e.g., wind turbine energy systems). this study, data-driven strategies are addressed under various faulty scenarios. A novel algorithm is by integrating fast Fourier transform uncorrelated multi-linear principal component analysis techniques in order achieve effective three-dimensional space visualization a...

This article concentrates on the event-driven controller design problem for a class of nonlinear single input output parametric systems with full state constraints. A varying threshold triggering mechanism is exploited, which makes communication more flexible. Moreover, from viewpoint energy conservation and consumption reduction, system capability becomes better owing to contribution proposed event-triggered mechanism. In meantime, developed control strategy can avoid Zeno behavior since...

The deployment of renewable energy in power systems may raise serious voltage instabilities. Electric vehicles (EVs), owing to their mobility and flexibility characteristics, can provide various ancillary services including active reactive power. However, the distributed control EVs under such scenarios is a complex decision-making problem with enormous dynamics uncertainties. Most existing literature employs model-based approaches formulate problems, which require full models are...

The large-scale integration of distributed energy resources into the industry enables fast transition to a decarbonized future but raises some potential challenges insecure and unreliable operations. Multi-energy Microgrids (MEMGs), as localized small multi-energy systems, can effectively integrate variety components with multiple sectors, which have been recently recognized valid solution improve operational security reliability. As result, massive amount research has conducted investigate...

Diagnosing potential faults is of great importance to ensure reliability battery management systems. This because a current or voltage sensor fault often results in an inaccurate state-of-charge estimate. A temperature will cause abnormal thermal management. internal resistance (BIR) can lead increase energy and power losses, capacity fading, further degradation health. In addition, frequent data transmission diagnosis unit waste communication resources. To this end, combined model-based...