Abstract Manufacturing systems are becoming more sophisticated and expensive, particularly with the development of intelligent industry. The complexity architecture concept Smart (SM) makes it vulnerable to several faults failures that impact entire behavior manufacturing system. It is crucial find detect any potential anomalies as soon possible because low tolerance for performance deteriorati...

Building sector account for significant global energy consumption and Heating Ventilation Air Conditioning (HVAC) systems contribute to the highest portion of building consumption. Therefore, potential saving by improving efficiency HVAC is huge various fault detection diagnosis (FDD) methods have been studied this purpose. Although amongst all types existing FDD methods, data-driven based ones...

This paper presents a Fault Detection and Diagnosis (FDD) method for stochastic nonlinear dynamic systems. Our contribution consists to show an another way of tackling the problem of the physical origin diagnosis of faults by combining the technique based on the innovations and the technique using the multiple Kalman filters for a nonlinear dynamic system strongly nonstationary. The usefulness ...

In this paper, we present a novel and effective fault detection diagnosis (FDD) method for wind energy converter (WEC) system with nominal power of 15 KW, which is designed to significantly reduce the complexity computation time possibly increase accuracy diagnosis. This strategy involves three significant steps: first, size reduction procedure applied training dataset, uses hierarchical K-mean...

Most observer-based methods applied in fault detection and diagnosis (FDD) schemes use the classical twodegrees of freedom observer structure in which a constant matrix is used to stabilize the error dynamics while a post filter helps to achieve some desired properties for the residual signal. In this paper, we consider the use of a more general framework which is the dynamic observer structure...

This review aims to provide an up-to-date, comprehensive, and systematic summary of fault detection diagnosis (FDD) in building systems. The latter was performed through a defined methodology with the final selection 221 studies. provides insights into four topics: (1) glossary framework FDD processes; (2) classification scheme using energy system terminologies as starting point; (3) data, code...

With the advent of Artificial Intelligence (AI) powered classification techniques, data-driven Fault Detection and Diagnosis (FDD) methods have become increasingly prominent in smart building implementation. Of these, cluster analysis is particularly promising for Building management system (BMS) data. This paper presents an unsupervised learning-based strategy detecting faults terminal air han...


 Due to the advancement of power electronics devices and control techniques, modular multilevel converter (MMC) has become most attractive for multiterminal direct current (MTDC) grids thanks its relevant features, such as modularity scalability. Despite their advantages, conventional MMCs face a major challenge with: i) fault-tolerant operation strategy; energy losses in conversion; iii)...

Heat, ventilation, and air conditioning (HVAC) systems are some of the most energy-intensive equipment in buildings their faulty or inefficient operation can significantly increase energy waste. Non-Intrusive Load Monitoring (NILM), which is a software-based tool, has been popular research area over last few decades. NILM play an important role providing future efficiency feedback developing fa...