This review aims to provide an up-to-date, comprehensive, and systematic summary of fault detection and diagnosis (FDD) in building systems. The latter was performed through a defined systematic methodology with the f...
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This review aims to provide an up-to-date, comprehensive, and systematic summary of fault detection and diagnosis (FDD) in building systems. The latter was performed through a defined systematic methodology with the final selection of 221 studies. This review provides insights into four topics: (1) glossary framework of the FDD processes;(2) a classification scheme using energy system terminologies as the starting point;(3) the data, code, and performance evaluation metrics used in the reviewed literature;and (4) future research outlooks. FDD is a known and well-developed field in the aerospace, energy, and automotive sector. Nevertheless, this study found that FDD for building systems is still at an early stage worldwide. This was evident through the ongoing development of algorithms for detecting and diagnosing faults in building systems and the inconsistent use of the terminologies and definitions. In addition, there was an apparent lack of data statements in the reviewed articles, which compromised the reproducibility, and thus the practical development in this field. Furthermore, as data drove the research activity, the found dataset repositories and open code are also presented in this review. Finally, all data and documentation presented in this review are open and available in a GitHub repository.
The postulation and experimental validation of a random vibration databased Functional Model based Method (FMBM) for multi-site damage localization, involving the determination of the number of damage locations and i...
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The postulation and experimental validation of a random vibration databased Functional Model based Method (FMBM) for multi-site damage localization, involving the determination of the number of damage locations and interval estimation of their coordinates, in presented. The method is based on Functional Models (FMs), along with proper statistical decision making and estimation techniques, and is capable of working with a limited number of random vibration signals under normal operating conditions. Two distinct versions of the method are introduced: A Forward or Multiple Model version which is based on multiple Functional Models, and a Backward or Single Model version based on a single counterpart. Both versions are experimentally validated and compared via hundreds of single-and double-site damage scenarios on the wing of a lab-scale aircraft skeleton structure, while a sensitivity analysis examining performance degradation for reduced numbers of training vibration signals is also undertaken. The results indicate high effectiveness in both determining the number of damage sites and estimating their precise coordinates along with their associated uncertainty.& nbsp;(c) 2021 Elsevier Ltd. All rights reserved.
The problem of random-vibration-based damage diagnosis, including detection and localization, for a lab-scale aircraft stabilizer structure is addressed. Diagnosis is based on the recently introduced Generalized Funct...
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The problem of random-vibration-based damage diagnosis, including detection and localization, for a lab-scale aircraft stabilizer structure is addressed. Diagnosis is based on the recently introduced Generalized Functional Model based Method, which utilizes a simple data-based model - instead of large-scale finite element type models - in the inspection phase and is capable of estimating the damage coordinates and their uncertainty region. The focus of the work is on assessing the achievable detection performance and localization accuracy under constraints on the number of deployed sensors and the excitation bandwidth, both reflecting practical limitations relating to potential in-flight implementation. The damage scenarios simulate local stiffness reduction via the addition of a small mass at any point on the structure. While the method has been recently employed with structures consisting of one-dimensional elements, it is presently and for the first time challenged with the considerably more complex problem of damage localization on a two-dimensional structural element. The method's details, including the transformation of functional boundary constraints into simple ones within the context of the associated optimization problem, are illustrated. The results obtained with a large number of experiments, using only two vibration sensors and limited, low-frequency signal bandwidth, demonstrate excellent damage detection and remarkably accurate localization, thus indicating the method's high potential for effective damage diagnosis.
This study focuses on railway vertical random vibration-based spectral analysis under normal operating conditions. Vibration acceleration measurements are acquired using sensors mounted on the car body, bogie frame, a...
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This study focuses on railway vertical random vibration-based spectral analysis under normal operating conditions. Vibration acceleration measurements are acquired using sensors mounted on the car body, bogie frame, axle bearing, and primary suspension of an Athens Metro vehicle running without passengers on a straight track. Two distinct track segments and four speeds (50, 60, 70, 80 km/h) are considered. The analysis focuses on the 0-1000 Hz frequency range using data-based non-parametric and parametric spectral estimation methods. The results indicate good agreement of the methods, the prominence of the 5-170 Hz frequency range along with higher frequencies at around 300 Hz and in the range of 600-750 Hz on the car body and the bogie frame vibration, the relatively minor dependency of the dynamics on the track segment, but their significant dependence on train speed. Yet, resonant frequencies are affected to a lesser extent, with at least 20 of them appearing as prominent.
In this paper, improved online inter-turn fault detection methods are proposed in order to take into account some design specifications related to recent Permanent Magnet Synchronous Machine (PMSM) topologies having m...
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ISBN:
(纸本)9781479901487;9781479901463
In this paper, improved online inter-turn fault detection methods are proposed in order to take into account some design specifications related to recent Permanent Magnet Synchronous Machine (PMSM) topologies having modular stator combined with Fractionnal Slot Concentrated Winding (FSCW). This winding allows compact PM motor mainly by reducing end windings. It is often associated with segmented stator in order to simplify the construction of the motor as in the case of Electro-Mechanical Actuators (EMA). This technique may lead to the presence of manufacturing faults such as additional air gaps between the various parts of the modular stator. This urges users to consider complex models of PMSM far removed from classical dq models. Consequently, undesirable harmonics, torque ripples can interfere with fault detection such as inter-turn fault detection algorithms. This paper proposes invasive methods interacting with PMSM control using both model-based and data-based methods in order to take into account these aspects for control and online inter-turn fault detection. Various experimental tests on an industrial EMA prototype validate the effectiveness of the proposed solution.
In this paper, improved online inter-turn fault detection methods are proposed in order to take into account some design specifications related to recent Permanent Magnet Synchronous Machine (PMSM) topologies having m...
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ISBN:
(纸本)9781479901463
In this paper, improved online inter-turn fault detection methods are proposed in order to take into account some design specifications related to recent Permanent Magnet Synchronous Machine (PMSM) topologies having modular stator combined with Fractionnal Slot Concentrated Winding (FSCW). This winding allows compact PM motor mainly by reducing end windings. It is often associated with segmented stator in order to simplify the construction of the motor as in the case of Electro-Mechanical Actuators (EMA). This technique may lead to the presence of manufacturing faults such as additional air gaps between the various parts of the modular stator. This urges users to consider complex models of PMSM far removed from classical dq models. Consequently, undesirable harmonics, torque ripples can interfere with fault detection such as inter-turn fault detection algorithms. This paper proposes invasive methods interacting with PMSM control using both model-based and data-based methods in order to take into account these aspects for control and online inter-turn fault detection. Various experimental tests on an industrial EMA prototype validate the effectiveness of the proposed solution.
Nowadays, with modern sensor technologies, the inputs, outputs and states of the system can be accurately measured. based on this fact, analyzing the properties of the system, which has unknown mathematical model, dir...
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Nowadays, with modern sensor technologies, the inputs, outputs and states of the system can be accurately measured. based on this fact, analyzing the properties of the system, which has unknown mathematical model, directly by using the measured data, has become feasible. In this paper, some data-based methods are proposed for state stability analysis of a class of nonlinear discrete-time systems. We also discuss the problem of finding the domain of attraction of the equilibrium point, using these data-based methods. (c) 2012 Elsevier Inc. All rights reserved.
In this work, we develop a data-based monitoring and reconfiguration system for a distributed model predictive control system in the presence of control actuator faults. Specifically, we first design fault detection f...
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In this work, we develop a data-based monitoring and reconfiguration system for a distributed model predictive control system in the presence of control actuator faults. Specifically, we first design fault detection filters and filter residuals, which are computed via exponentially weighted moving average, to effectively detect faults. Then, we propose a fault isolation approach that uses adaptive fault isolation time windows whose length depends on the rate of change of the fault residuals to quickly and accurately isolate actuator faults. Simultaneously, we estimate the magnitudes of the faults using a least-squares method and based on the estimated fault values, we design appropriate control system reconfiguration (fault-tolerant control) strategies to handle the actuator faults and maintain the closed-loop system state within a desired operating region. A nonlinear chemical process example is used to demonstrate the approach. Copyright (C) 2011 John Wiley & Sons, Ltd.
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