Article
Engineering, Chemical
Philipp Wetterich, Maximilian M. G. Kuhr, Peter F. Pelz
Summary: Modular process plants provide flexibility and efficiency, and this paper proposes an approach for condition monitoring and diagnosis by deriving model-based symptoms from a few measurements and observers based on manufacturer's knowledge.
Article
Green & Sustainable Science & Technology
Phong B. Dao
Summary: This paper presents a new approach for condition monitoring and fault diagnosis of wind turbines based on structural break detection in SCADA data. The method uses the Chow test to assess the stability of regression coefficients in a multiple linear regression model, enabling the detection of faults in the wind turbine.
Article
Energy & Fuels
Yue Cui, Pramod Bangalore, Lina Bertling Tjernberg
Summary: This paper proposes a fault detection framework for the condition monitoring of wind turbines, which models and analyzes data from supervisory control systems. The framework uses recurrent neural networks to model normal behaviors and introduces a two-stage threshold method to determine the current operation status.
Review
Engineering, Electrical & Electronic
Nuno M. A. Freire, Antonio J. Marques Cardoso
Summary: This paper provides a comprehensive review of fault detection and condition monitoring in wind turbines and PMSGs, with a focus on electromagnetic measurement-based methods. It introduces the basics of PMSG operation and terminology to serve as a reference for engineers and data scientists, and also discusses the experiences and research challenges related to stator winding failures.
Article
Engineering, Multidisciplinary
Tomasz Nowakowski, Franciszek Tomaszewski, Pawel Komorski, Grzegorz M. Szymanski
Summary: The article presents the genesis of a method to diagnose a tram transmission based on acoustic signals from the track position. The influence of a damaged gearbox on acoustic phenomena near the tram line, specifically changes in psychoacoustic indicators, was demonstrated. Nonstationary acoustic signals were analyzed using empirical mode decomposition. The developed quantitative measure served as a classifier in decision trees. An effective tree was selected based on calculated diagnostic indicators, and an algorithm to diagnose the tram transmission without mounting equipment on the vehicle was developed.
Article
Energy & Fuels
Noman Shabbir, Lauri Kutt, Bilal Asad, Muhammad Jawad, Muhammad Naveed Iqbal, Kamran Daniel
Summary: This article discusses research on power quality issues in modern power systems, focusing on improving power factor to mitigate the adverse effects of inductive loads on the system. Through the analysis of real-time data from a frequency converter, a hybrid solution based on wavelet transform and Fourier transform is proposed for diagnosing the causes of motor failure in ventilation systems.
Review
Computer Science, Information Systems
Tarek Berghout, Mohamed Benbouzid, Toufik Bentrcia, Wei Hong Lim, Yassine Amirat
Summary: Condition monitoring of industrial processes is crucial for minimizing downtime and increasing productivity through accurate maintenance planning. Advanced intelligent learning systems enable effective fault diagnosis and identification. Smart industrial infrastructure technology allows for fully decentralized distributed computing for fault diagnosis tasks.
Review
Computer Science, Information Systems
Muhammad Zakir Shaikh, Zeeshan Ahmed, Bhawani Shankar Chowdhry, Enrique Nava Baro, Tanweer Hussain, Muhammad Aslam Uqaili, Sanaullah Mehran, Dileep Kumar, Ali Akber Shah
Summary: In recent decades, there has been a demand for faster, longer, and safer railway networks, which poses challenges for condition monitoring systems in modern railway vehicles. Critical parts like wheels degrade over time due to various reasons, leading to wheel defects and ultimately derailment. Research has been conducted to develop efficient condition monitoring systems, and commercial products incorporating sensors for data collection have been deployed. However, there is still a research gap in developing advanced onboard systems. This paper reviews the existing wayside systems, identifies their advantages and disadvantages compared to onboard systems, and critically analyzes data acquisition and analysis methods.
Article
Chemistry, Analytical
Catarina S. Monteiro, Antonio Rodrigues, Duarte Viveiros, Cassiano Linhares, Helder Mendes, Susana O. Silva, Paulo V. S. Marques, Sergio M. O. Tavares, Orlando Frazao
Summary: Optical fiber sensors embedded in power transformers can provide structural monitoring through vibration analysis, potentially enabling real-time monitoring and playing a critical role in the operation of power systems.
Article
Engineering, Electrical & Electronic
Moein Ghadrdan, Saeed Peyghami, Hossein Mokhtari, Frede Blaabjerg
Summary: This article proposes a simple converter-level structure for measuring the ON-state voltage of every power semiconductor in a three-phase conventional inverter. The proposed circuit enables the development of a hand-held portable monitoring device that can be used independently of the converter. Detailed information is given on how to design and select the components of the proposed monitoring system, along with its optimal operating conditions.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Article
Automation & Control Systems
Enes Ugur, Chi Xu, Fei Yang, Shi Pu, Bilal Akin
Summary: This article introduces a new complete condition monitoring method that can independently monitor the threshold voltage drift and packaging degradation of SiC MOSFETs. By monitoring the reverse body diode voltage drop, the health status of the device can be accurately assessed.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Review
Engineering, Electrical & Electronic
Xiaotian Zhang, Yihua Hu, Chao Gong, Jiamei Deng, Gaolin Wang
Summary: This article reviews AI-based approaches in condition monitoring and fault diagnosis of electric powertrains used in electric vehicles (EVs). AI can solve issues that traditional methods cannot and provides better performance and application prospects. The article comprehensively discusses the motivation, advantages, limitations, and challenges of AI-supported methods through case summaries, classification, comparisons, and quantitative analyses. It concludes by proposing future trends in this field.
IEEE SENSORS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Weiwei Zhang, Yigang He, Jianfei Chen, Bolun Du
Summary: This article presents a unified open-circuit FD and CM method for the 3L-T inverter based on the proposed on-state voltage measurement circuit (OVMC). The designed OVMC separates all the OVs and actual switching state information with a few devices and terminals. The proposed method for fault locating requires only a straightforward lookup table without complicated feature extraction and threshold setting steps, and the FD results would help to correct the OV distribution.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Article
Computer Science, Information Systems
Ciro Attaianese, Matilde D'Arpino, Mauro Di Monaco, Luigi Pio Di Noia
Summary: This paper presents a model-based method for detecting phase current sensor gain faults in a Permanent Magnet Synchronous Motor (PMSM) drive with Field Oriented Control (FOC). By using a mathematical model and low-computation algorithm, the faulty sensors can be detected, isolated, and their gain values estimated based on measured phase currents and motor speed. The performance of the model and diagnostic algorithm is verified through numerical and experimental results.
Article
Automation & Control Systems
Yayu Peng, Wei Qiao, Liyan Qu
Summary: This article proposes a compressive sensing-based missing-data-tolerant fault detection method for remote condition monitoring of wind turbines. It increases the sparsity of the collected signals, samples them using a compressive-sensing-based algorithm, and reconstructs the signals at the receiving end to detect faults in wind turbines.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Engineering, Electrical & Electronic
Eric A. Ponce, Steven B. Leeb, Peter A. Lindahl
Summary: This article introduces the use and functionality of positive displacement water meters, proposing a cost-effective method for equipping them with digital flow rate measurement capabilities. It discusses magnetic field modeling and associated algorithms, with verification through experimental results.
IEEE SENSORS JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Joseph W. O'Connell, Daisy H. Green, Brian T. Mills, Andrew Moeller, Stephen Kidwell, Kahyun Lee, Lukasz Huchel, Steven B. Leeb
Summary: Ventilation systems require periodic preventive maintenance, but critical systems may have unpredictable maintenance intervals. This paper introduces hardware instrumentation and signal processing algorithm to nonintrusively track rotor slot harmonics of multiple fan motors, combined with a physics-based model to monitor maintenance conditions.
IEEE SENSORS JOURNAL
(2021)
Article
Automation & Control Systems
Manuel Gutierrez, Peter A. Lindahl, Steven B. Leeb
Summary: This article presents an equivalent circuit model for limited-bandwidth constant power loads (CPLs) and analyzes a control architecture based on this model. The control scheme limits the impact of CPLs on system stability by emulating the internal damping of CPLs, thus supporting utility operation.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Engineering, Electrical & Electronic
Thomas C. Krause, Katherine Camenzind, Daisy H. Green, Andrew Moeller, Lukasz Huchel, Steven B. Leeb
Summary: This article presents a sensor topology and signal processing technique for noncontact measurement of polyphase line-to-line voltage. Conductive plates around the exterior of a three-phase cable form a circuit that can be used to disaggregate the ac voltages in the cable. Fully differential transimpedance amplifiers detect capacitive currents that can be related mathematically to line-to-line voltages. Sensor calibration and line-to-line voltage reconstruction results are presented.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Electrical & Electronic
Aaron W. Langham, Daisy H. Green, Steven B. Leeb
Summary: This article explores the use of averaging techniques to enhance signal fidelity when sampling quasi-periodic signals, focusing on evaluating power consumption and harmonic content drawn by ac loads using spectral envelope preprocessing. The article derives a statistical characterization of the preprocessor system's resolution in relation to analog input noise and extends the concept of effective number of bit (ENOB) to this averaging system. Design trade-offs in quantization bits, sampling frequency, noise level, and minimum resolvable transient are investigated. The conclusions drawn here apply to any system that involves the extraction of spectral envelopes.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Electrical & Electronic
Thomas C. Krause, Lukasz Huchel, Daisy H. Green, Kahyun Lee, Steven B. Leeb
Summary: English Summary: Motor current signature analysis (MCSA) techniques are used for slip estimation, fault detection, and motor diagnostics by measuring slip-related current signals in the supply lines of a squirrel-cage induction machine (SCIM). In a traditional setup, current sensors are physically installed close to the machine to directly measure the machine currents. For grid-connected SCIMs, a single power monitor can potentially perform nonintrusive MCSA for a collection of SCIMs powered by a common electrical service. This article demonstrates the hardware, modeling, and experimental results for nonintrusive MCSA and investigates its applicability compared to traditional MCSA.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Automation & Control Systems
Daisy H. Green, Aaron W. Langham, Rebecca A. Agustin, Devin W. Quinn, Steven B. Leeb
Summary: Sensing solutions offer various measurements for electromechanical load monitoring and diagnostics, which can be utilized for energy management, maintenance, and fault detection. However, many feature selection methods do not consider concept drift and evolving behavior. This article presents a method to evaluate load separability in a feature space while accounting for changing operating conditions. The method is validated using a four-year load dataset.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Artificial Intelligence
Daisy H. Green, Aaron W. Langham, Rebecca A. Agustin, Devin W. Quinn, Steven B. Leeb
Summary: This work presents a framework for adaptive classification and drift detection in practical machine learning applications for streaming data. The framework is demonstrated using nonintrusive load monitoring (NILM) as a case study.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Information Systems
Daisy H. Green, Aaron W. Langham, Devin W. Quinn, Thomas C. Krause, Steven R. Shaw, Steven B. Leeb
Summary: This paper presents statistical feature extraction techniques for identifying fluctuating power behavior of loads, and evaluates an energy estimation procedure for load operation on a shipboard microgrid and laboratory machine shop equipment.
Article
Engineering, Electrical & Electronic
Daisy H. Green, Devin W. Quinn, Samuel Madden, Peter A. Lindahl, Steven B. Leeb
Summary: The gradual environmental degradation of materials can lead to corrosion and mechanical failures of electrical loads, resulting in the loss of system capability and the possibility of electrical fires. Nonintrusive electrical monitoring can detect the impending electrical failures. This article demonstrates techniques for decoding the electrical signatures that lead to progressive failure, using observations of the degradation and failure of copper-sheathed jacket water heaters as examples.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Electrical & Electronic
Brian T. Mills, Daisy H. Green, John S. Donnal, Steven B. Leeb
Summary: This article introduces practical techniques to time-align measurements collected on a ring bus in order to monitor individual load power consumption. Marine microgrids are used to illustrate the presented time-alignment algorithms, and the results are demonstrated on ring-bus microgrid hardware.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Electrical & Electronic
Patrick Wang, Joseph Zatarski, Arijit Banerjee, John S. Donnal
Summary: This article presents an approach to monitor the condition of SiC MOSFETs by estimating the gate-leakage current in situ using an add-on circuit. Experimental validation shows that this method can alleviate the reliability concerns of SiC MOSFETs and opens up possibilities for device-level prognostics.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Electrical & Electronic
Erik K. Saathoff, Daisy H. Green, Rebecca A. Agustin, Joseph W. O'Connell, Steven B. Leeb
Summary: Training the load identification algorithm for a power-system monitor begins with observing the loads and using a phase-controlled switch to account for the effects of source and line impedance on load transients. The system presented in the article can provide training data for machine learning algorithms and be used as the foundation for a smart switch in grid applications for automatic demand response control.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
