Article
Automation & Control Systems
Junchao Guo, Qingbo He, Dong Zhen, Fengshou Gu
Summary: In this paper, a novel robust modulation spectrum correlation (RMSC) gram algorithm is proposed for fault extraction. The signal is demodulated into a bispectral map display containing fundamental and modulation frequency through RMSC, and RMSC subbands are obtained using a finite impulse response filter on the fundamental frequency. The fault feature index of subbands under healthy and fault conditions is calculated to generate RMSC gram using its failure signature ratio (FSR). The RMSC with the maximum FSR is selected as the optimal subband, and envelope analysis is performed on the subband to extract fault features.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Review
Energy & Fuels
Sudip Halder, Sunil Bhat, Daria Zychma, Pawel Sowa
Summary: This paper provides an overview of available fault detection methods for the broken rotor bar problem in induction motors. Despite being less common, this fault can cause catastrophic failures in motors, especially large ones. The study uses current signal analysis to extract probable defect signatures for confirming rotor bar fracture.
Article
Computer Science, Artificial Intelligence
Junho Lee, Younghun Lee, Namsu Kim
Summary: With the increasing demand for automated manufacturing and logistics system, research on interior permanent magnet synchronous motors (IPMSMs) has become active due to their high torque density and efficiency. Therefore, fault diagnosis technology for electric motors is crucial for detecting abnormal signs and evaluating fault type and severity, enabling condition-based maintenance of smart manufacturing and logistics systems. This study focuses on the fault characteristics of parallel misalignment, analyzing the frequency domain and load fluctuation size. Modeling, simulation, and experimental verification were conducted on an IPMSM drive system controlled by an inverter. Results show that motor current signal analysis can effectively detect misalignment faults under various conditions.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Chemistry, Analytical
Mohamed Habib Farhat, Len Gelman, Gerard Conaghan, Winston Kluis, Andrew Ball
Summary: This study proposed, investigated, and experimentally validated two new diagnostic technologies to diagnose a lack of lubrication in gear motor systems using motor current signature analysis (MCSA) for the first time worldwide. The effectiveness of these technologies was evaluated and compared for different gear lubrication levels, and the results confirmed their high effectiveness for diagnosing a lack of oil lubrication in gearmotor systems.
Article
Computer Science, Interdisciplinary Applications
Izaz Raouf, Hyewon Lee, Heung Soo Kim
Summary: Prognostic and health management (PHM) is an important field in modern industry, and the rotate vector (RV) reducer is a widely used mechanical component. To detect faults in RV reducer, researchers introduce a novel approach using an embedded electrical current system and machine learning for fault classification. The feasibility of this approach is justified through the improvement of evaluating parameters.
JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING
(2022)
Article
Automation & Control Systems
Jorge Bonet-Jara, Joan Pons-Llinares, Konstantinos N. Gyftakis
Summary: Early detection of interturn faults in electrical machines is crucial, but the severity and speed of fault evolution can vary depending on the machine application. This article focuses on submersible induction motors for deep-well pumps, which have slower fault evolution due to their water-cooling system. The article investigates the use of principal slot harmonics as reliable indicators for early fault detection and proposes a diagnostic scheme based on monitoring these harmonics along with voltage and current unbalance indexes.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Engineering, Industrial
Miguel Angel Bermeo-Ayerbe, Vincent Cocquempot, Carlos Ocampo-Martinez, Javier Diaz-Rozo
Summary: This research proposes a non-intrusive condition monitoring method to estimate the remaining useful life (RUL) of the most critical component in an electromechanical system. It focuses on monitoring the characteristic frequencies from the torque oscillations transmitted via the stator currents. By processing current signals and using exponential regressions, the RUL can be estimated along with its confidence bounds. The methodology achieved high accuracy in anticipating bearing failures with a significant lead time.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Geochemistry & Geophysics
Victor de Bronac de Vazelhes, G. Beaudoin, I. McMartin, O. Cote-Mantha, N. Boulianne-Verschelden
Summary: The nature and thickness of glacial sediments in the Amaruq gold deposit area in northern Canada impact the characteristics of mineralized dispersal trains. Principal Component Analysis identified a signature of gold mineralization associating various elements, similar to other lode gold geochemical signatures. This signature follows a NNW dispersal trend and aligns with regional and local ice-flow indicators.
JOURNAL OF GEOCHEMICAL EXPLORATION
(2021)
Article
Energy & Fuels
Pawel Ewert, Teresa Orlowska-Kowalska, Kamila Jankowska
Summary: This paper focuses on the possibility of detecting mechanical damage in permanent magnet synchronous motors (PMSMs) caused by bearing failures, by analyzing mechanical vibrations with the support of shallow neural networks (NNs). The extraction of diagnostic symptoms was conducted using Fast Fourier Transform (FFT) and Hilbert transform (HT) to obtain the envelope signal, which was then analyzed further.
Article
Engineering, Mechanical
Kai Xu, Xing Wu, Dongxiao Wang, Xiaoqin Liu
Summary: In this study, a detection method for bolt loosening of industrial robot joint based on electromechanical modeling and motor current signature analysis (MCSA) is proposed. The method utilizes the time-frequency features of the motor current to detect loosening and achieves effective results.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Multidisciplinary Sciences
Mehdi Tabasi, Mohammad Mostafavi, Mansour Ojaghi
Summary: Motor current signature analysis is a useful method for detecting incipient faults in induction motors. However, the harmonic components introduced by local defects in the rolling-element bearing are usually too weak to be detected using common signal processing techniques such as the fast Fourier transform.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
Article
Chemistry, Multidisciplinary
Diego Brito, Rene Gomez, Gonzalo Carvajal, Lorenzo Reyes-Chamorro, Guillermo Ramirez
Summary: This paper presents a novel study using motor current signature analysis (MCSA) to identify impact frequency in rotary-percussion drilling. The envelope approach is found to be the most robust method for real-time implementation, offering simplicity and wide coverage. The proposed MCSA methods show feasibility to be integrated into Measurement-While-Drilling (MWD) systems, enhancing drilling condition monitoring and rock mass characterization.
APPLIED SCIENCES-BASEL
(2023)
Article
Biochemistry & Molecular Biology
Yuxiang Fan, Xinyu Peng, Yubo Wang, Baoqin Li, Gang Zhao
Summary: The study revealed that HDAC1 was overexpressed in glioma, while HDAC11 was downregulated in glioblastoma. The expression of HDAC family was associated with glioma grade and genetic mutations. HDAC1 was identified as a prognostic and immune infiltration indicator in glioma.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2021)
Proceedings Paper
Engineering, Electrical & Electronic
Howard W. Penrose
Summary: The paper discusses the common issues of magnetic wedge loss and coil movement in wind power asynchronous generators, and proposes a method of detecting and addressing problems in a timely manner through Electrical Signature Analysis.
2021 IEEE ELECTRICAL INSULATION CONFERENCE (EIC)
(2021)
Article
Engineering, Aerospace
John C. Bennett
Summary: A technique has been developed to analyze the free-space acoustic signature of the Rolls-Royce Merlin engine for diagnostic information on its performance. Data extraction and processing generate multi-level color images of individual cylinder firings, showing variations at different engine speeds. The technique also allows for the identification of specific engine faults related to the imaging results.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING
(2022)